Predictive Modeling In Healthcare and The Role of Digitization

The digital transformation of the healthcare industry is moving at an accelerated pace as healthcare facilities continue to reap its benefits in operational management, epidemiology, and personal medicine. And one subset of Digitization that is proving to be extremely useful is the integration of predictive modeling and analytics in healthcare.

Predictive modeling refers to the use of historical data or available data to make predictions of future events which helps with making better decisions. It is also used to troubleshoot or anticipate future behavioral patterns or outcomes using multivariate data sets or events.

In medicine, predictive models are being used to see into the future to define expected trends in operational management, and patient care both on an individual level and at a larger scale. While in pharmaceutical laboratories, predictive models are being used to predict future demand, enhance productivity, and in advanced planning and scheduling.

The Importance of Digital Transformation and Predictive Modeling In Healthcare

The digitization of healthcare data has provided the public with access to large repositories of health-related matters. Today, with a smartphone any individual can look up symptoms and seek medical advice from the comfort of their homes.

Digitization has also put patient data and educational resources at the fingertips of healthcare providers worldwide. Although these are excellent examples of the advantages of digitization, predictive maintenance takes things to the next level. With predictive modeling comes the option to enhance operational management in ways never experienced before.

One example is the use of predictive models to analyze patient no-shows, treatment schedules, and optimizing hospital resources. In 2018, The Elmont Teaching Health Center introduced the use of predictive modeling to track its patient no-shows which were costing the center money. To better anticipate no-shows and plan accordingly, the health center turned to predictive modeling.

With the hospital’s historical data, a predictive model for the patients most likely to not show up was developed. This model was then simulated against hospital resources with the aim of rerouting these resources to other patients. The result was a 14% reduction in its no-show rates which saved the healthcare center hundreds of thousands of dollars caused by patients.

Another important scenario which predictive models and simulations help with is in dealing with optimizing operations in emergency departments. First and foremost, it is important to establish the importance of timing and resource availability within emergency units to understand the importance of predictive modeling.

Medical errors in emergency rooms and inadequate facility allocation cause approximately 250,000 deaths annually in the United States and 1,500, 000 globally. Although solving the issues related to emergency care does not rely on operational management alone, the ability to predict the number of emergencies, allocate resources, and develop functional schedules can ease important challenges. These challenges include facility overcrowding and overworking emergency healthcare providers.

An example of how predictive models and Simulation aids emergency response can be seen from the example of Wake Forest Baptist Health Center. In this case study, predictive models of its patient inflows were developed and used to analyze the rate of patient inflow and how best to allocate hospital resources to cater for both emergency patients and others.

With the model, the hospital was able to manage the inflow of patients and emergency situations. The simulation results also provided actionable intelligence to hospital management which helped with crafting better policies for dealing with emergency and excessive patient visits.

Another example of the importance of predictive modeling in healthcare is its use in developing strategies for handling complex scenarios. One such scenario is the evacuation of patients with mobility challenges during disasters. The experiences of hospitals during Hurricane Harvey and Katrina led a team of researchers from John Hopkins University to apply simulation and scheduling to simplifying evacuation efforts.

In this case study, agent-based modeling was used to model the complex individual assets and varying conditions of patients into an evacuation simulation. The simulation also integrated micro-scale models of agents and mesoscale models of population densities to understand the relationship and behavioral patterns of the diverse agents within an evacuating system.

The result of the study showed the extent to which macroscopic and mesosscopic models produce system-level behaviors in agent-based models.

The Significance of Predictive Modeling In Pharmaceutical Facilities

As with every manufacturing-based industry, the pharmaceutical industry relies on managing logistics chains, optimizing shop floor operations, and manufacturing workstations to meet customer demand. Thus, the integration of predictive modeling and simulation has significant roles to play in delivering actionable intelligence and insights into optimizing production.

With a simulation or digital twin software, comprehensive models of a pharmaceutical manufacturing facility can be developed. This predictive model can be used to introduce external phenomena such as increased demand and scheduling delays to understand their impact on the manufacturing process.

In this model of a digital twin developed using Simio Simulation Software, the activities and capacity of a manufacturing facility can be seen as well as the discrete events happening within the shop floor. Within a digital twin, predictive simulations can be run to optimize the facilities supply chain with the aim of optimizing productivity. And according to RevCycle, healthcare facilities including big pharma can save approximately $9 million yearly in supply chain management costs. These benefits also apply to health-related manufacturing niches including biomedical devices, dental, and orthodontics manufacturers.

The Risks of Relying on Predictive Modeling In Healthcare

The healthcare industry is built around catering to humans and human relationships which means data analytics alone will not cut it. According to Deloitte, the integration of digital technologies in healthcare comes with risks such as moral hazards, privacy issues, and a lack of regulation.

Here, moral hazards refer to the machine-like application of healthcare in complex situations. With predictive analysis, patients in critical condition may be overlooked in order to ensure healthcare professionals have more time for other patients. A lack of regulation can also see harmful policies sneak into healthcare with the aim of managing resources and making the most profit.

Privacy concerns are also significant challenges that digitization brings up. One example is the loss of patient data by the National Health Service (NHS) due to a ransomware attack. In this instance, over 300,000 patients across the United Kingdom were affected by the security breach. Thus, cybersecurity must be taken into consideration when integrating predictive modeling and simulation in healthcare.

Conclusion

The importance of predictive modeling and simulation in healthcare, as well as, its risks will be discussed in more details at the Simio Sync Digital Transformation Event. Dean O’Neil of John Hopkins University will speak on ‘Building Capacity for Healthcare Modeling and Simulation’.

His session will provide in-depth information concerning the application of simulation at his time at the John Hopkins University Applied Physics Laboratory. Attendees will go away with about applicable modeling and simulation strategies which can be used to optimize their healthcare facilities. Simio Sync Conference will take place on the 4th to 5th of May in Pittsburgh. You can register for an early bird ticket here.

Best Answers to Commonly Asked Risk Analysis Questions

Many managers don’t understand what exactly risk analysis is.  We put together some of the most common questions with responses for you.

What does the risk percentage mean?

The risk percentage approximates the on-time probability for an order with appropriate consideration of the number of replications or “experiments.”  It tells the user how confident they can be in meeting the due date given how many trials they have conducted. 

How does Simio calculate the on-time probability?

Simio adjusts from a base rate of 50% with each risk replication.  If an order is on time in an individual replication, Simio updates the probability, increasing it closer to 100%.  If the order is late, Simio decreases the probability closer to 0%.  Each replication is an experiment that provides new information about the likelihood of success or failure.  More experiments mean more confidence in the answer.

Why is the base rate 50%?

Before any plan is generated or any activity is simulated, there is no information about the order other than the possible outcomes.  Because there are only two outcomes that matter (on time or not), the base rate is set to 50%.

I have an overdue order in my system.  Why is it not always 0%?

Because the calculation is an adjustment of a base rate of 50%, Simio needs a lot of evidence before it will guarantee that an order will be late (or on time for that matter).  If the user runs 1000 replications, and the result is late in all of them, Simio will reflect a 0% on time probability. 

What formula does Simio use to calculate the probability?

For the statistics experts, Simio uses a binomial proportion confidence internal formula known as the Wilson Score.  We report the midpoint of the confidence interval as the risk measure.

Why not just report the outcome of the replications as the probability (e.g., if 9 of 10 are on time, report 90% on time probability)?

This was the original implementation.  However, it gives a false sense of confidence and can be misleading.  A single replication would always yield either 100% on time or 0% on time.  We wanted the answer to also give decision makers a sense of how confident they could be in the answer.  Using the Wilson Score, a single replication will yield a result of 60% at best and 40% at worst (using 95% confidence level).  This helps the decision maker identify that they have a very small sample of data and would encourage them to run additional replications. 

Can you give me an example of how this works?

Risk analysis can be demonstrated using any scheduling example.  It is best viewed in the Entity Gantt.  In the screenshots below, we’ve included 2 orders from the Candy Manufacturing Scheduling example.  One of the orders is overdue (will be late always), and the other has plenty of time (will be on time always).

The base rate is 50%.  After 1 replication, Simio updates the probabilities.  Order 1 now has a 60% on time probability.  Order 2 has a 40% on time probability.

After 2 replications, 67% and 33%:

After 5 replications, 78% and 22%:

After 100 replications, 98% and 2%:

Finally, after 1000 replications, 100% and 0%:

How many replications should I run?

By default, we suggest 10 replications (and 95% confidence level).  With these settings, a risk measure of 86% is a good sign, while 14% is a bad one.  Beyond the default settings, there are several additional factors which are dependent on the situation and use case.  One of these factors is slack time (the time between estimated completion and due date).  On the Gantt, slack time is the distance between the grey marker and the green marker.  If the slack time is large, a single replication may suffice.  If the slack time is small, additional replications will help identify if the order is in trouble or not. 

Now that I know my risk, what can I do about it?

Depending on your position in the organization (and therefore your decision rights), you can change either the design or operation of the system.  Example design changes include things like adding another assembly line or buying another forklift.  These changes are long term and may require approvals for capital expenditure (which the model facilitates by quantifying the impact of the expenditure).  Example operational changes include things like adding overtime, expediting a material, or changing order priorities, quantities, due dates etc.  Bridging the gap between design and operation are the dispatching rules, which relate to overall business objectives.  They are also flexible parameters which control how Simio chooses the next job from a queue (e.g., earliest due date, least setup, critical ratio, etc.).  All of these parameters influence risk and can be changed, provided that the user has the authority to change them.

Will Simio choose the best design and operation for me?

Decision rights and business processes have far reaching consequences.  A floor manager can probably authorize overtime if the schedule looks risky.  He probably cannot buy a piece of equipment.  To change a priority or a due date, he probably needs to consult with the commercial team and/or account managers.  To expedite a material, he probably needs to communicate with the procurement team.  To make a capital expenditure (i.e., change system design), he probably needs executive/financial approval.  Our solution respects those boundaries.  We treat priorities, due dates, etc. as inputs rather than outputs.  Any of these parameters can be changed by the appropriate decision maker.  They should not be changed by the tool without consent.  Simio assists the decision maker (at any level in the organization) by exposing the true consequences.

With so many choices, how can I quickly explore the consequences across multiple scenarios?

The experiment runner is used to explore consequences (which we call Responses) across multiple scenarios where a user can influence the parameters mentioned above (which we call Controls).  If the solution space is very large (i.e., there are many controls with a wide range of acceptable values), we recommend using OptQuest to automate the search of the solution space based on single or multiple objectives (e.g., low cost and high service level).  OptQuest uses a Tabu search which learns how the control values influence the objectives as it explores the solution space.

How often should I run these type of experiments?

Experiments are most relevant to design choices.  Operational decisions have many hard constraints which cannot be easily influenced.  For example, though Simio will allow you to adjust material receipt dates of critical materials and show you the impact on the schedule, many of them are inflexible and out of control of planner or even the business.  If you ask OptQuest how much inventory you would like to have, it will tell you, but this information adds no value because it is not actionable in the short term.  The planners need to work with what they have and make the best of it.  In practical application, we recommend running large experiments to explore design decisions on a monthly or quarterly basis.

Integrating Digital Transformation to Enhance Overall Equipment and Facility Efficiency

The digital transformation of traditional business process and the assets that run them have become one of the raves of the moment. A Forbes-backed research highlights just how popular the topic of digital transformation and the tools needed to accomplish it has become. Statistics like the fact that 55% of business intended to adopt digitization strategies in 2018 which grew to 91% in 2019 highlights just how popular this transformation has become.

The reason for its increased adoption rate is the ease it brings to managing business operations, facilitating growth, and a healthy return on investments made on digital transformation. The numbers from the 2019 digital business survey prove these benefits outlined earlier to be true. 35% of organizations have experienced revenue growth while 67% believe it has helped them deliver better services to customers. But despite its popularity, the adoption of digital transformation brings up a multitude of question many enterprises still struggle to answer. This post will answer some of the more important questions with special emphasis on facility management and efficiency.

What is Digital Transformation?

Digital transformation refers to the integration of digital technologies into business operations to change how an enterprise operates and delivers value to its customers or clients. Digital technologies generally refer to devices and tools that enable access to the internet thus its use allows organizations to bring operational processes to cyberspace.

The above definition is a simpler version of what digital transformation is about but because digital transformation looks different for every company and industrial niche, other definitions exist. In terms of enhancing equipment and facility efficiency levels, the definition by the Agile Elephant better encapsulates its meaning. Here, digital transformation is defined as digital practices that ‘involve a change in leadership thinking, the encouragement of innovation and new business models, incorporating digitization of assets, and increased use of technology to improve an organizations entire operations.’

In facility management, assets refer to the equipment, tools, and operation stations within the facility while new business models and innovation refer to the integration of digital technology concepts. These concepts can be the digital twin, discrete event simulation or predictive analysis.

What is Overall Equipment and Facility Efficiency?

Productivity within manufacturing facilities and warehouses are generally measured using the overall equipment effectiveness (OEE) concept. This concept measures the maximum output machines can achieve and compares subsequent output to the optimized value. In cases where the machine or equipment falls short, the OEE falls from 100% and the production cycle may be termed unproductive.

The OEE is calculated using three separate components within facilities and these are:

  • Availability – This focuses on the percentage of scheduled time an operation is available to function.
  • Performance – This refers to the speed at which work centers compared to the actual speed it was designed to achieve
  • Quality – This refers to the number of goods produced and the quality levels compared to optimal production qualities.

Although the OEE process is quite popular and has proved to be efficient, a critical analysis shows that it does not take into consideration some important metrics. OEE calculations do not include the state of the shop floor, material handling processes, and connections to both upstream and downstream performances. This is why its effectiveness as a measuring tool has been lampooned by a plethora of manufacturers with skin in the game.

Criticism of OEE as a performance measurement tool include its lack of ability to breakdown or access granular information in facilities and its lack of multi-dimensionality. The fact that it struggles with identifying real areas that require improvement within facilities is also a deterrent to its efficiency in analyzing factory performances. And this is where digital transformation comes into play.

Digital Transformation and its Ability to Enhance Facility Efficiency

The ability to digitize assets within manufacturing shop floors have created an environment where granular data can be collected from the deepest parts of today’s facilities. With the data collected due to digital transformation, a clearer picture of how a facility function can be gotten. But the digitization of traditional manufacturing processes and operations have also been a source of debate for diverse professionals due to certain difficulties. These difficulties include assessing data from legacy or dumb assets, managing communications across diverse supply chains, and bringing captured data together to make sense of complex facility operations.

To manage these challenges, diverse emerging technologies have been built around each of them. In terms of capturing data from legacy assets, the use of smart edge technologies that can be attached to assets is currently eliminating this challenge. While standards and communication protocols such as those from the OPC foundation is solving the issue of communication across both smart and dumb assets. Finally, to make sense from the captured data in order to enhance shop floor activities, digital twin technology provides a streamlined approach to monitoring and managing facilities using captured data.

With these emerging technologies, detailed insight at the granular level can be assessed about a particular facility. More importantly, these technologies attached to digital transformation can be used to enhance operational processes by delivering real-time scheduling, analyzing complex processes, and simulating applicable solutions to manufacturing shortcomings.

Discrete Event Simulation and Enhancing Facility Efficiency

Discrete event simulation (DES) tools such as Simio are some of the emerging technologies that play important roles in transforming traditional factory or facility processes. The introduction of DES can help with mapping out previous event schedules to create optimized scheduling templates that can speed up production processes.

DES tools or software can analyze both minor processes that are subsets of a large one, as well as, the entire complex system to produce schedules that optimize these processes. An example of this was the integration of Simio by Diamond-Head Associates, a steel tubing manufacturing company. The challenges the steel tubing manufacturer faced involved meeting production schedules due to a very complex production process with hundreds of production variables.

With the aid of Simio simulation software and the digital transformation it brings, Diamond-Head associates were able to utilize the large data sets produced by the varying production processes. With this simulation model, optimized schedules built for its manufacturing processes were created and this helped with making real-time businesses decisions. The steel tubing manufacturer successfully reduced the time it took to make a decision from an hour and a half to approximately 10 minutes.

This case study highlights how digital transformation can be used to enhance facility efficiency in diverse ways. These ways include optimizing scheduling procedures and drastically reducing the time needed to come up with accurate solutions to complex manufacturing-related scheduling processes.

Enhancing Facility Productivity with the Digital Twin

Another aspect of digital transformation is the use of digital twin technologies to develop digital representations of physical objects and processes. It is important to note that the digital twin does more than a 3D scanner which simply recreates physical objects into digital models. With the digital twin, complex systems can be represented in digital form including the capture of data produced by assets within the system.

The digital twin ecosystem can also be used to conduct simulations that drive machine and facility performance, real-time scheduling, and predictive analytical processes. Thus highlighting how digital transformation provides a basis for receiving business insights that change the leadership of an organization thinks and make decisions.

An example that highlights the application of digital twin technology to enhance productivity or facility efficiency is that of CKE Holdings Inc. CKE Holdings is the parent company of restaurants such as Hardee’s and Carl’s Jr. Earlier this year, the enterprise was interested in providing efficient shop floors or restaurant spaces for its employees to increase productivity levels, train new employees, and deliver better services to its customers. To achieve its aims, the organization turned to the digital twin and augmented reality to aid its business processes.

Once again, it is worth noting that both the digital twin and virtual reality tools are digital transformation tools. And with these tools, CKE Holdings Inc. succeeded in developing optimized restaurants with shop floor plans that played to the strength of its employees. The digital twin was also used to test and implement new products at a much faster rate than the traditional processes previously employed by the enterprise.

The end result was a user-friendly kitchen layout that delivered innovation in how CE Holdings restaurants function. The use of augmented reality also added another dimension to the training of new employees. The use of technology ensured new employees learnt through live practical involvement without any of the consequences attached to failure. This also reduced the hours experienced workers spent getting new employees up to speed within the restaurants. Thus highlighting another aspect in which digital transformation can be applied to drive facility efficiency levels.

The Benefits of Digital Transformation to Manufacturing and Production-Based Facilities

The examples outlined already spell out the benefits of digital transformation and its role in enhancing overall equipment and facility effectiveness levels. But, it is only right to compare and highlight what digital transformation brings to the table against the traditional OEE calculations still used within many shop floors.

  • A Complete Picture – Unlike OEE calculations which rely solely on manufacturing data produced from equipment and tools, digital transformation technologies can capture every aspect of the production process. This includes capturing data from the diverse algorithms, scheduling details, assets, sub-systems, and events that occur within the shop floor. This makes the level of details provided by digital twin environments superior to analyzing and enhancing facility productivity.
  • Improved Customer Strategy – Digital transformation enables the capture of data highlighting customer satisfaction with end products. This information can also be integrated into the manufacturing circle to ensure customers get nothing but the best service. This means with digital transformation the feedback of customers and employees can be used to enhance production facility processes.
  • Improved Employee Retention Strategy – The manufacturing industry is notorious for its high employee turnover rate due to diverse factors that make it unattractive to the new generation of workers. The integration of digital transformation can enhance workplace layout, as well as, bring a more modern and captivating process to manufacturing. These enhancements can reduce the turnover rate and get the younger generation interested in manufacturing.
  • Enabling Innovation – The increased adoption rate of industry 4.0 business concepts and models in manufacturing means businesses must adapt if they intend to retain their competitive edges. Digital transformation offers a pathway to innovating legacy business process and increasing an enterprise’s ability to stay competitive in a changing manufacturing industry.

The Next Steps

The advantages digital transformation brings to enhancing facility efficiency comes with a butterfly effect that affects leadership, innovation, and problem-solving activities. Although the integration process involves technical knowledge of applying digital twin technologies and simulation software, these skills can be acquired with a little effort.

Simio Fundamentals Course offer businesses and other organizations with the opportunity to train staffs about digital transformation and its specific techniques. You can also choose to register employees to participate in the upcoming Simio Sync Digital Transformation 2020 Conference to learn more about digitally transforming your business processes and how to reap the rewards.

How Do You Create a Digital Twin – 5 Things to Know

The Digital Twin is reminiscent of the early days of the personal computer in many ways. Initially, creating a digital twin required excessive computing power and multiple engineers working round the clock to develop digital representations of physical models. And just like the personal computer, technological advancement led to the creation of cloud-based digital twin solutions which made it possible for everyone to explore digital transformation and it is benefits.

Today, the digital twin market is expected to grow exponentially and this growth is being driven by the approximately 20 billion sensors and endpoints around the world. Advancements in IoT and IIoT have also played a role in increasing the adoption rate of digital twin technology which are some of the reasons why digital representations of almost any entity or process can be created today.

The benefits of the digital twin include the ability to make real-time decisions, receive insight from complex processes or systems, and plan better for the future. You can explore how digital twin can help your enterprise or individual pursuits by reading relevant case studies here. Now, to reap these benefits, a digital twin of a chosen process, object, facility, or system must be created which is what this post is all about. Thus, if you have ever wondered what it takes to develop a digital twin then bookmarking this is recommended.

5 Things You Should Know About Creating a Digital Twin

The task of creating a digital twin may sound daunting but like most activities diving in headfirst without overthinking simplifies the process. Once you have the required tools needed to create a digital twin, the supporting technologies such as Simio provides you with prompts and interactive information needed to complete the process. To successfully create a digital twin, here is what you need to know and the resources you need to have:

  1. Defining the System – The first step to creating a digital twin is defining the system, process or object to be digitized. To do this, an understanding of the entity is required and this can only be achieved through data capture. Thus, data defines the system to be digitized and introduced into the digital space.

The data capture process is generally fluid in nature and depends on the entity or system being considered. For manufacturing facilities, the data that defines a system or process can be gotten from assets within a facility these assets include original equipment, shop floor layouts, workstations, and IoT devices. Data from these assets are captured using smart edge devices, RFIDs, human-machine interfaces and other technologies that drive data collection.

With physical objects such as vehicles, data capture is done through sensors, actuators, controllers, and other smart edge devices within the system. 3D scanners can also be used to extract point clouds when digitizing small to medium-sized objects. The successful capture of the data a system or object produces defines the system and is the first step to creating a digital twin.

  • The Identity of Things – One of the benefits of a digital twin is the ability to automate processes and develop simulations that analyze how a system will operate under diverse constraints. This means the system or facility to be digitized must have its own unique identity which ensures its actions are autonomous when it is introduced into a system.

To achieve this, many digital twin platforms make use of decentralized identifiers which verify the digital identity of a self-sovereign object or facility. For example, when developing a digital twin of a facility, the entire system will have its own unique identity and assets within the facility are verified with unique identities to ensure their actions are autonomous when executing simulations within the digital twin environment.

  • An Intuitive Digital Twin Interface – Another important element or choice to make when creating a digital twin is selecting a technology or software that can help you achieve your goals. You must be clear about how the technology can help you achieve your goals of a digital twin. Some things you need to consider when choosing a digital twin software or platform include:
  • How the software handles the flow of data from the IoT devices or facility and other enterprise systems needed to understand and digitize the chosen process.
  • You need to understand how the software recreates physical objects or assets into its digital ecosystem. Some technologies support the use of 3D models and animations when recreating entities while others do not deliver that level of clarity.
  • When digitizing complex systems with hundreds of variables that produce large data sets, the computing resources needed to create and manage a digital twin is increased. This makes computing power and resources a key consideration when choosing a digital twin platform or solution. The best options are scalable digital twin technologies that leverage the cloud to deliver its services.
  • An intuitive digital twin solution also simplifies the process of creating digital representations of physical assets. The technology should also be able to understand the data produced across the life-cycle of an asset or at least integrate the tools that can manage the identity of assets within the digital twin.
  • Another key consideration is the functions you expect the digital twin to perform. If it is to serve as a monitoring tool for facilities or for predictive maintenance, a limited digital twin software can be used while for simulations and scheduling a more advanced technology will be required.
  • Start Small with Implementation – When taking on the implementation of digital twin technology, it is recommended you start small. This means monitoring the performance of simple components or a single IoT device within a system and expand with time. This hands-on approach is the best way to understand how the digital twin functions and how it can be used to manage larger systems according to your requirements.

With this knowledge, you can then choose to explore the more sophisticated aspects or functions the digital twin offers such as running complex discrete event simulations and scheduling tasks. A step by step approach to implementing or creating a digital twin provides more learning opportunities than initiating a rip and replace approach when developing one.

  • Understand the Security ConsiderationsAccording to Gartner, there will be 50 billion connected devices and 215 trillion stable IoT connections in 2020. As stated earlier the increased adoption rate of digital twin technology and the connected systems around the world bring up security challenges. These security considerations also affect the digital twin due to the constant transfer of data from the physical asset or process to the digital twin ecosystems.

When creating a digital twin, a plan must be in place to handle secure communication channels across networks and other vulnerabilities. To effectively do this, an understanding of the different communication protocols used within a system is required. This is why when choosing a digital twin technology, security challenges and how the platform mitigates risk must also be considered.

Creating a Digital Twin with Simio

Simio digital twin technology provides an extensive framework for creating digital twins of physical processes and facilities. The key considerations such as 3D representation, animation, scaling up functions, and simulation can be achieved within Simio’s environment.

If properly created, the digital twin can be used to drive data analytics initiatives, predictive maintenance, design layouts, and simulate diverse working scenarios. Thus, anyone or an enterprise can explore the benefits of the digital twin using Simio to create digital representations of complex systems or simpler ones. You can learn more about using Simio to create digital twin representations by registering for the Simio Fundamentals Course.

Top Trends in Simulation and Digital Twins Technology for 2020

Digital Twins refers to the digital representations of people, processes, and things. It is used to analyze operations and receive insight into complex processes. As 2019 comes to an end, the need to define digital twin technology still exists and hopefully by this time next year, its growth and popularity will make this need obsolete…

In 2018, digital twins were included as a top technology trend by the big names covering the tech industry. According to Orbis research, the digital twin market is expected to grow by 35% within a 5-year time frame and 2020 is right in the middle of this period. But before highlighting the trends to expect in 2020, it is only right to do a recap of the year so far. This is to note if earlier predictions have come to pass before mapping the future.

In terms of popularity, coverage of the digital twins is definitely on the right track as continuous studies by Gartner and other publications show. Today, many professionals across the technical and non-technical divide understand the digital twin concept and how it can be used to drive business processes and concepts. This is why many industries are currently integrating digital twins to bolster business insight and understand data.

The biggest adopters of digital twin technology in the geographical sense remains North America. Enterprises within the US and Canada currently leads the way in terms of adopting digital twin technology. North America accounts for approximately 59% of the digital twin market and economy while Europe and the Asian pacific comes next.

The very nature of the digital twin and simulation, as well as, the solutions they provide makes them attractive business tools for the manufacturing industry and this fact is backed up by data. The manufacturing industry’s affinity to digital twins is powered by Industry 4.0 and the varied ongoing processes that occur within shop floors. The use of smart edge devices, equipment, robots, AI, and automation also fits nicely into the digital twin concept thus making it attractive to manufacturers.

In 2019, manufacturers account for approximately 36% of the digital twin market. Other industries such as the energy and power industry, Aerospace, Automobile and Oil & Gas complete the top five industries who make use of the digital twin to enhance operations. Analyzing this trend highlights the fact that digital twins are important to simplifying complex processes where hundreds or thousands of variables and relationships are needed to successfully accomplish set tasks.

Is the Digital Twin for Only Production-based Industries?

Although the Oil & Gas industry, as well as, the energy and power sector are not tagged as manufacturing industries, a case can be made for it. Therefore, many may assume or wonder if digital twin technology is only useful within production-based industries where discrete or process manufacturing takes place. And the answer is No.

The digital twin is also being used in other industry verticals such as the hospitality industry and in restaurants. One example is the use of Simio by CKE Holdings Inc. to ease workloads in its Carl’s Jr and Hardee’s restaurants. The Digital twin is also being used to support discrete event simulations in hotels, real-estate, and tolling facilities.

The use of interconnected devices and automation within service and hospitality businesses are the driving forces behind the adoption of digital twin within a variety of industries. And the coming year is expected to witness continuous growth as more industries and professionals understand what the digital twin brings to the table.

Top 5 Trends for the Digital Twins and Simulation Technology for 2020

Interrelated Technologies will Boost Adoption Rate – The growth and maturity of interrelated technologies such as 3D printing, metal printing, and mapping will play a part in accelerating the adoption rate of digital twins in 2020. This is because of the need to monitor and consistently improve these technologies and the systems that drive them.

Using 3D printing as an example, many manufacturing outfits are currently making use of 3D printing clusters to speed up their production requirements. 3D printing clusters or farms refers to facilities where hundreds of 3D printers function simultaneously to manufacture physical items. Although these 3D printing clusters have dedicated software for managing the printing process, material delivery, scheduling, and managing the entire supply chain within these facilities are handled manually.

Digital twin solutions can eliminate the manual management and handling process in 3D printing farms to great effect. If properly executed, a digital twin of a large scale 3D printing cluster will provide a data-driven approach to optimize supply, scheduling and the manufacturing process. This will reduce expenditure including the energy expended in 3D printing cluster facilities.

Industry 4.0 will Continue to Drive Adoption – The growth in Industry 4.0 and the devices, as well as, communication channels driving the smart factory is expected to increase the adoption of digital twin solutions. In 2019, Industry 4.0 witnessed the creation of new standards from the OPC Foundation that supports the collection of data from the deepest corners of brownfield facilities. These data were collected from dumb equipment with legacy technologies using smart edge and embedded devices.

The success of this approach, means that digital twin technology can now integrate the data collected from dumb or legacy equipment when developing digital representations. This increases the accuracy levels of the representations thereby enhancing simulation results and scheduling plans. Thus, increasingly accurate digital twin ecosystems and results will create more use cases that will drive the adoption of digital twins in 2020.

IoT and IIoT to Drive Digital Twin Adoption Rate – The move to more interconnected environments across both manufacturing and service-based industries also have roles to play in 2020. As stated earlier, Industry 4.0 will enhance the adoption of digital twin technologies and this also true for the industrial internet of things (IIoT). The widespread adoption of IoT and IIoT devices or equipment have created a race to develop the best management solution to monitor interconnected activities.

This creates an avenue which digital twin service providers are currently taking advantage of and will continue to do so in 2020. The ability of the digital twin to create digital representations of IIoT devices and also integrate the data they produce creates multiple use cases enterprises will explore in the coming years. These use cases include running simulations in complex interconnected facilities to produce accurate results or to access processes that involve the use of IIoT technologies.

Digital Twin for Cybersecurity Challenges – With every passing decade, the cybersecurity challenges enterprises face keeps changing. The millennium brought Trojan horses and other viruses which were effectively stopped with anti-virus software apps and by 2010, attackers pivoted to using phishing attacks and malware. Today, ransomware, spyware, DDoS, and business email compromise attacks have become the new challenges enterprises face. Thus highlighting the ever-changing landscape of cyber threats.

To cater to these threats and attacks, digital twin solutions will be enlisted by enterprises in 2020. In this scenario, the digital twin will be used as a penetration testing tool to simulate the effects of successful data breaches or ransomware to an organizations business processes. Within the digital twin environment, attacks to core equipment can be simulated and the result will be a response pattern that ensures the crippled equipment does not lead to extended downtime.

2020 will also be expected to witness an increase in the cybersecurity threats facing cloud-based digital twin solutions. Thus, more secure communication protocols and standards regulating data use will be developed to protect enterprises making use of digital twin technology. This means developers and service providers will have an increased role to play in securing digital twin environments.

Simulation-based Scheduling – The drive to deliver real-time scheduling is expected to continue in 2020 as enterprises seek more accuracy with managing business process. The need for real-time scheduling is also driven by how enterprises intend to apply simulation and digital twin tools. An example includes the need to make business decisions in real-time, handle unforeseen occurrences such as machine downtime, and reschedule operations.

These challenges fall into the category of issues discrete event simulation (DES) software can handle. Once the required data is accessible, DES and digital twin applications can conduct simulations in real-time and provide accurate solutions to dealing with changing scenarios also in real-time. This will drastically reduce downtime and enhance performance within facilities and warehouses.

Although some DES software offers real-time simulation scheduling, many are still process-based scheduling applications and this is set to change in 2020.

Quantum Computing – If real-time simulation, scheduling, and process management is to be achieved, then digital twin solutions must take advantage of the speed, scalability, and high-performance quantum computing offers. Today, digital twin solutions currently leverage the cloud to provide stable and scalable services to enterprises and only a few integrate the use of high-performing computers to enhance or manage really large workloads.

In 2020, further strides will be made to speed up simulations within digital twin environments using high-performing computers. The success of this initiative will speed up real-time scheduling and complex process management for the foreseeable future.

Planning for 2020…

The benefits of the digital twin have played an important role in ensuring its adoption across diverse industries and the expected trends of 2020 will continue the increased adoption rate that came with 2019. Although digital twin solutions have become more interactive and intuitive to use, enterprises still require the assistance of experienced professionals to get the best out of their digital twin environment and this is where Simio can help.

IT managers, cybersecurity experts, and project managers can take advantage of the Simio Fundamentals Course to learn more about simulation and Digital Twin technology including its application in real-life scenarios.

Simio Showcases the Digital Twin at INFORMS Annual Meeting 2019 – A Recap

The INFORMS Annual Meeting for 2019 has come and gone with multiple keynotes shared, workshop activities, and hundreds of excellent companies sharing their experiences and solutions from brightly colored booths. Once again, Simio was at the thick of things evangelizing the benefits of simulation and Digital Twin technology to the world. As with all annual meetings, the focus was on the strides been made in operational research and analytics. And the meeting provided the chance to explore emerging technologies and its applications across all ‘works of life’.

The term ‘all works of life’ wasn’t used lightly as sessions covering social media analytics and e-learning to applying analytics to human trafficking were explored. As for Simio, our role was somewhere in the middle and as stated earlier, our participation was centered around the digital twin. But before going into details of how the event panned out and Simio’s roles, here is an outline of what the INFORMS Annual Meeting is about for interested individuals.

INFORMS Annual Meeting

INFORMS which stands for the Institute for Operations Research and the Management Sciences is an umbrella organization for professionals plying their trade in operations research and analytics. INFORMS currently boasts of approximately 12,500 members across the globe which highlights its global or international reach.

The organization also sets standards and guidelines to ensure research and analytics within its field are ethically done. To bring its thousands of members together under one roof, the INFORMS Annual Meeting event was created and it holds once a year. The event features keynote sessions, workshops, publication presentations, and an exhibition area for member and enterprises to showcase their wares.

The INFORMS Annual Meeting also coincides with its community service drive to assist non-profit organizations with meeting their obligations. This is done through the INFORMS Pro Bono Analytics section of the organization. If you are wondering why the information about Pro Bono Analytics is included here, then I ask for patience as it will all make sense in the end.

Now to the annual meeting of 2019!

The 2019 INFORMS Annual Meeting was a 3-day event which ran from the 20th of October to the 23rd. This year’s event was definitely a success as more than 5,000 people breezed through the different sessions, exhibition areas, workshops, and lunch areas throughout the 3-day event. The convention center buzzed with activities through these days and we are proud to say Simio capitalized on these activities in different ways. Our participation included a dedicated Simio booth highlighting the use of Simio digital twin technology, a session handled by Jason, and workshop presentations from Renee.

Keynote Sessions and Workshops of Note at the INFORMS Annual Meeting

Tens of session covering operations research and analytics were covered throughout the event which makes mentioning and discussing every one of them impossible. So, the focus will be on simulation, digital transformation, cloud computing, and digital twin sessions.

One of the exciting sessions within the above category was the session about the computational infrastructure for operations research, COIN-OR, initiative. The IBM project focuses on providing open-source technologies solely for computational operations research. The end goal is to provide an open-source library of tools which will ensure researches do not have to start from scratch when handling complex research. This creates a foundation that will be built on and maintained by researchers over the years.

The session ‘Robust Optimization and Learning Under Uncertainty’ was also interesting as it discussed the challenges stakeholders face with decision-making and policy creation. Han Yu, a PhD student at the University of California spoke about how important data collection, and an understanding of history should drive real-world decision-making. The session also discussed how modeling and robust optimization techniques can enhance the decision-making process.

Other notable sessions highlighted or raised questions about the role digital twin and simulation could play in enhancing agriculture and the healthcare industry. According to Greg from Syngenta, AI, computer vision, and bioINFORMSatics modelling currently assist Syngenta with making data-driven seed selections and breeding. This raises the question of the role of the digital twin in agriculture which may be explored in other blog posts.

In the ‘Healthcare Modeling and Optimization’ session, Dr. Zlatana Nenova spoke about the role modeling and data analytics play in improving healthcare. Her speech also touched on the use of digital technology to analyze medical care policies for both off and on-site healthcare delivery. In terms of on-site healthcare, there are certainly diverse ways the healthcare industry can benefit from digital twin technology. Although this was not covered in this year’s event, it highlights the possibilities of applying digital twin to the healthcare industry.

Simio’s Events at the INFORMS Annual Meeting

Now, to Simio and our role at the INFORMS conference. In last year’s event, Ms. Renee Thiesing, the VP of Strategic Alliances,  spoke excellently on the role Simio plays in driven discrete event simulation and the digital transformation of brownfield systems as the move to Industry 4.0 continues. She also highlighted the importance of real-time event scheduling and how Simio can help enterprises solve real-time scheduling challenges using Simio.

In this year’s event, Ms. Renee built on her earlier foundation by focusing on the digital twin capabilities of Simio and its application in diverse industries. Her session titled ‘New Innovations: Cloud Computing, Real-Time Scheduling, Industry 4.0 and more’ discussed how Simio leverages cloud computing to deliver high-performing scheduling and simulations.

Through the session, she discussed how Simio leverages the computing power of Microsoft Azure to support complex applications. Simio’s compatibility with Schneider Electric’s Wonderware was also discussed in detail. This includes the leveraging of Wonderware to achieve detailed production scheduling in real-time, as well as, manage real-time risk analysis. The new Simio features such as Simio’s cloud portal and OptQuest were also covered during her workshop. She highlighted OptQuest abilities to optimize scheduling and simulation with the aim of delivering optimal solutions to complex business problems.

Jason Ceresoli also spoke on the benefits of using Simio’s 3D modelling capabilities to solve real—world problems. His presentation covered Simio’s features for system design and operation. Practical examples of how Simio’s rapid 3D modeling, planning and scheduling, and optimization capabilities can be used by enterprises were also discussed by Jason. Finally, his session highlighted the difference between Simio and other simulation tools with a focus on how professional researchers and analysts can use these features. 

Our participation at the INFORMS Annual Meeting will not be complete without recounting our experiences at booth 28 in the exhibition area. The targeted message used in the Simio booth drew its own audience of professionals, entrepreneurs and business representatives interested in the digital twin. This gave us the opportunity to showcase Simio’s features and real-world applications to interested individuals. We can categorically say our booth played a role in the sales leads and opportunities we got from the event.

Simio and the Pro Bono Analytics Event

I remember introducing you to the INFORMS Pro Bono Analytics and now here we are! This year, Pro Bono Analytics partnered with a Seattle-based non-profit organization, FareStart, to assist individuals interested in building careers in food service and culinary arts. At this year’s INFORMS Annual Meeting, Simio alongside other participants made donations to the FareStart initiative.

The event was a success and according to Elise Tinseth, Community Engagement Manager with FareStart, shared, “The INFORMS Pro Bono micro-volunteer opportunity of creating hygiene kits is impactful to eliminating barriers our students who are experience poverty and homelessness have to getting jobs in the food service industry.’ She also thanked everyone who made out time and donated resources to help FareStart meet its goals.

INFORMS Annual Meeting Awards and the Future

And lastly, the INFORMS Annual Meeting Awards. Although Simio did not bag any of the awards, the pomp and pageantry, as well as, the strides made by researchers are worthy of a mention in this post. Hopefully, the prize for teaching operations research and management science may be ours. That being said, the 2019 event was a success and Simio will continue to be a part of the INFORMS Annual meeting for the foreseeable future.

Simio Training and Certification – Introducing Simio Fundamentals

Learn from Simulation Experts, Advance Your Skills and Knowledge.

Organizations across every industry need individuals with simulation, modelling, and digital transformation skills to help transform their business processes. Simio Fundamentals will help you learn, relearn, and validate your simulation and modelling abilities with this introductory course. Simio Fundamentals is an online course which consists of 14 modules. Each module was designed and created by simulation experts including Dr Jeffery Smith, a professional with decades of experience in teaching and solving simulation-related problems.

The 14 modules that make up the Simio Fundamentals training are all video instructions consisting of practical information that eases you into the technical aspects of simulation, animation, and modeling. Although the course is focused on Simio’s simulation software, the knowledge and skillset to be gained can be applied in other simulation ecosystems. This is why interested students, educators, employers, and employees should view this course as one that covers the fundamentals of simulation.

Is the Simio Fundamentals Course for You?

The course was designed for Simio customers and students across the globe who currently use Simio simulation software and digital twin solutions for learning and simulating business processes. Individuals within this category can up their skills and accomplish more with Simio by taking advantage of the information and practical solutions in the fourteen modules.

Simulation, modeling, and digital twin solutions are currently being employed across diverse industries to monitor and manage complex processes, as well as, implement new business concepts. Thus, system integrators, project managers, data analyst, and engineers can also take advantage of the information in this course. Simo Fundamentals offer you, regardless of your experience with simulation, the opportunity to re-learn simulation from scratch and an entry point to mastering digital twin technologies.

Employees can also take advantage of the certification opportunity that comes with completing the Simio Fundamental course and the certification process that comes with it. A Simio Fundamental Certification will highlight your abilities in simulation and modeling tasks. The certification will also highlight your ability to apply simulation processes in solving complex business operational challenges and real-world problems. Employers can also take advantage of this opportunity to teach staff about the basics of simulation and train them on its application within a facility. This ensures everyone is on the same page and understand the integration of simulation technology into business processes.

How Important Is Simio Fundamentals to Your Industry?

Simulation and its interrelated fields such as scheduling, digital twin, and process control are used across every industrial niche where business operations take place. This means regardless of your industry, some knowledge of simulation and its processes will be helpful to an individual’s career and business growth. 

In the tech or IT industry, simulation is widely used to test and explore different business processes, implement new strategies, and analyze prototypes. The Simio Fundamentals course include modules that cover modeling and animation which are important for testing new ideas, hardware designs, and IoT devices to note how they will function in the real world. This is where knowledge in simulation and taking advantage of the Simio Fundamentals course comes into play.

In education, Simio simulation software is currently being used in 800 universities across the globe to teach students about STEM-related concepts. This includes modeling and animation which are staples of engineering and computer science. Educators and students can now learn the fundamentals of simulation and working with Simio by studying the modules in this course.

In banking and finance, simulation is being used to design check out points to deliver enhanced customer services to clients. Simulation and modelling can also be used to organize the layout of banking halls to optimize productivity within a workforce. Managers, stakeholders, and decision-makers can take advantage of this course to learn about simulation and its ability to gain business insights from the banking and finance industry.

Taking a look at manufacturing, simulation plays an important role in streamlining manufacturing process including production, material handling, and the varying relationships that go on in today’s shop floors. The rise of industry 4.0 has also created an avenue were simulation thrives. With knowledge of simulation, manufacturers can implement new strategies and industry 4.0 business concepts in facilities. Simulation also provides the opportunity to explore concepts of generative design for complex systems and products.

Like the manufacturing industry, production-based industries such as in Oil & Gas, mining, and the pharmaceutical industry, simulation also has an important role to play. Knowledge of simulation can be applied to enhancing material handling processes, digitizing shop floors, and determining time dependencies and other related modeling tasks. The facility management and hospitality industry can also take advantage of simulation to implement new processes and monitor the diverse ongoing systems within a facility. The Simio Fundamentals course provide the foundation needed to apply simulation and modelling techniques in these industries.

Gaining an understanding of Simio through the Simio Fundamentals Course gives you the knowledge needed to apply simulation in your industry however you choose. This includes solving real-world problems, educating students, and implementing new business concepts.

Introducing Simio Fundamentals

Simio Fundamentals is a course offered by Simio University and it covers the fundamental of simulation and Simio. The course is made up of 14 modules which include the following subject matters:

  1. An Introduction to Simulation – This introduces simulation and defines its application and impact.
  2. Introduction to Simio & Success Tips – This provides an overview of Simio, its interface, and simulation tools.
  3. Introduction to Animation – This introduces basic animation concepts and the use of animations in Simio.
  4. Simio Modelling Framework – This introduces Simio’ modelling framework, interfaces, and commands.
  5. Simio Standard Library Fixed Objects – This module includes workshops that introduce the resources available to you when using Simio.
  6. Balking and Reneging – A workshop that focuses on balking and reneging.
  7. Task Sequences – This introduces the basics of task sequencing and an introduction to materials.
  8. Controlling Movement
  9. Material Handling – This introduces the use of Simio to simulate material handling and the basics of manual and automated material handling.
  10. Working with Model Data – This introduces the management of data tables and scheduling with Simio.
  11. Process Logic – This module is an introduction to processes and its related concepts.
  12. Debugging Tools and Techniques – This introduces the debugging techniques available with Simio.
  13. Optimizing with OptQuest
  14. Building Custom Object Definitions – This introduces you to Simio’s object libraries and how to make use of them.

Each module was designed by simulation experts and Simio professionals who have acquired real-world experience with applying simulation in diverse situations for decades. The modules are in video form and each module runs for 35 to 90 minutes depending on the topic. Simio Fundamentals modules are designed in such a way that you can complete the entire course within two weeks. The modules also consist of 23 workshops that provide you with the opportunity to get hands-on with simulation with Simio. Educators can also make use of these workshops as teaching tools for students.

It is also important to note that this course is licensed for and per individual use. Thus, educators who intend to use it in their classrooms can contact us to learn more about how we can help. Subscribing to the course gives you access to the videos and workshops in every module. This means you can pace the learning process to fit your schedule. If you would like continuous access to the course, you can choose the licensing option that makes this possible.

Next Steps…

The benefits of having an understanding of simulation and its application in the real world are varied for students and individuals. These benefits include:

  • Providing prospective employees with an entry point into industries that deal with simulation.
  • Helping students to learn about simulation with Simio and prepare them for the challenges in today’s workspaces.
  • Receiving business insights from simulated models of real-world processes.
  • Acquiring a Simio certificate that proves you understand simulation and its applications.

Simio Training and Certification – Introducing Simio FundamentalsThese benefits are why over 800 universities and hundreds of enterprises make use of simulation and Simio simulation solutions to solve complex challenges. Get started with Simio and simulation today by registering for the Simio Fundamentals course.

Integrating Simulation and Digital Twin Technology in the Hospitality Industry

The numbers are in and they do look good for the hospitality industry which consists of hotels, restaurants, and other hospitality-related services. According to Forbes, profitability in the hospitality industry is finally on the increase after the slump of previous years. The report further stated that the net profit margins for full-service restaurants grew by approximately 6% which is 3.8% more than the previous year. The National Restaurant Association expects this growth to continue but early wins must also be consolidated if this is to be achieved. And this is where Digital Twin Technology comes into play.

With the expected growth figures also comes challenges and in the hospitality industry, these challenges generally include fending off the competition and enhancing operations to reap increased rewards. In terms of competition in the hospitality industry, the following statistics paint a clearer picture. In 2018, approximately 60,000 new restaurants and lounges were opened in the United States while 50,000 either filed in for chapter 11 or were closed down for other reasons. Although at the end of the year, the industry grew with the addition of 10,000 restaurants, this mass closure still highlights the competitive nature of the industry.

The competitiveness in the hospitality industry is turning many small and large scale stakeholders to turn to emerging technologies to ease operational deficiencies. This is why today, the hospitality industry has become one of the major drivers of innovation in robotics, artificial intelligence, digital visualization, and the internet of things (IoT). The aim is to collect data from every aspect of a hotel or restaurants operational chain and use that data to receive the business insights needed to stay ahead of the competition.

Today, most hotels make use of interconnected devices to simply customer requests and analyze their peculiarities in order to deliver bespoke services. Examples of this include the use of concierge robots by the Hilton group and the design of smart hotels by Marriot and other stakeholders.

And to what benefits?

Integrating digital technology in the hospitality industry has led to a 40% increase in revenue for online travel agencies (OTAs) who streamline and personalize their services for customers. In brick and mortar hospitality facilities like the Marriot hotels, its financial report of 2018, highlighted a 38 percent increase in revenue with emerging technologies playing a starring role in simplifying operations. This led Arne Sorenson, CEO of Marriot, to state that ‘digital transformation is not only speeding up every aspect of our business, but it is also broadening operations’. And this transformation, as well as, the benefits they bring can be broadened much further with the integration of Digital Twin technology.

What is A Digital Twin?

A digital twin refers to virtual representations of physical products, systems, facilities and the processes that occur in them. The technology can be used to create digital replicas of actual physical assets and processes and also integrate potential assets onto the created virtual environment. This means every asset that functions in a shop floor including devices or equipment and all business operation or process can be recreated in a digital environment.

Digital twin environments also create an enabling environment for testing new business policies, operations, and assets to access their performance levels before any physical implementation is undertaken. When put beside the recent adoption of smart technology in the hospitality industry, it is easy to see why digital twin technology is the solution every stakeholder has been waiting for to broaden business operations.

One of the major features of the digital twin is its ability to virtualize every asset and process that occurs in an environment. In the hospitality industry, these assets may include; the smart devices used in rooms, check-in and check-out points, robots, the equipment used for logistics and supply chain management, inventories, and every process that produces data. This means when correctly deployed, a digital twin can recreate assets and processes from the deepest parts of a hospitality system in a digital ecosystem.

The Digital Twin and Enhancing the Hospitality Industry

The easiest way to understand how digital twin technologies can be leveraged to gain an edge over the stiff competition in the hospitality industry is through case studies and CKE Restaurants Holdings, Inc. provides an example.

CKE Restaurants Holdings, Inc. digital twin Story is one that showcases how harnessing digital twin technology and virtual reality can be used to test and implement new operational policies within the hospitality industry. In its case, CKE recreated hundreds of assets and kitchen configurations using the digital twin with the aim of deciding the best configuration that will increase productivity in its Carl’s Jr and Hardee’s restaurants. With the aid of Simio’s digital twin solutions, restaurant floors and kitchens were digitized which provided the perfect environment for reorganizing shop floor assets to reduce employee traffic and create an enabling environment for customers.

To achieve the level of detail needed to accomplish this task, CKE had mapped out every production aspect that occurs within a restaurant down to the plate cleaning process. With this data, accurate simulations could be executed which yielded highly-accurate results. Thus, integrating new equipment and testing how they function with other variables and assets within the restaurant was made possible. This meant receiving accurate business insight into new policies and the effects of introducing new assets before effecting a physical implementation.

According to Forbes, the integration of Simio’s digital twin helped CKE Restaurants, Holding, Inc. manage hundreds of simulations that consisted of the introduction of diverse assets and processes into the digital model. This allowed the restaurant to predict the effects of introducing approximately ten new equipment to the shop floor, as well as, test the efficiency levels of five layouts for the kitchen. The use of a digital twin also helped analyze new designs that would assist CKE with easing the workload on employees which would lead to higher employee retention in an industry notorious for low retention rates.

The example of CKE Holdings, Inc. still leaves the question of if the digital twin can enhance operations in larger more complex facilities. The short answer to this is, definitely yes!

Digital twin technologies have been made use of in large industrial settings such as Nestlé’s and Boeing facilities to implement new ideas and enhance production. Although these examples highlight the importance of digital twin technology, the focus is on the hospitality industry which leads to the longer answer.

In the large hotels with 300 rooms and above, more operational processes occur that dwarf the example highlighted in the CKE case study. These processes include; logistics and supply chain management, tracking the orchestration of hundreds of customers, power consumption, and correctly assigning workplace assets to meet demand. Other smaller systems within a large hotel’s immediate environment are the valet and parking system, concierge system, and manual workflows.

As stated earlier, digital twin solutions are capable of recreating diverse assets, processes and system in a virtual environment when correctly applied. This actually makes the digital twin a solution custom-built for large hotels where the need to keep track of multiple processes within a system while implementing new ideas is a regular occurrence. With the aid of the digital twin, every data produced in large facilities can be collected and analyzed against the different assets within the system. This gives the system integrator or manager a contextual insight into every aspect of running a hotel facility in real-time.

Furthermore, the digital twin of large hotel facilities can be used to run both discrete and continuous event simulations to better understand the events occurring in different systems. A discrete event simulation can be used to test how the implementation of building of an additional check-out point at the parking lot will ease driving and foot traffic before a physical implementation is considered. Also, a simulation of the power consumption that occurs within the facilities can provide insight into which assets or processes can be periodically shutdown to reduce consumption.

The benefits of Adopting Digital Twin in the Hospitality Industry

 Although the earlier case studies provide an insight into the benefits of the digital twin to the hospitality industry, more information is sometimes needed when making decisions. In this case, the decision to be made is choosing to enhance operations using digital twin solutions.

One of the important benefits of integrating a digital twin is the clarity of purpose it provides to facility managers and hotel owners. The use of a digital twin means decisions no longer has to be made in the dark. An accurate digital twin built with every asset, process, and data coming from a hotel or restaurant is the perfect environment for testing out anything before implementation. The test can be as extensive as analyzing the effects of a new equipment transportation system or how automating a business process will turn out. The test can also be as little as analyzing how changes in shelf heights will increase employee productivity.

Another important challenge hospitality businesses face involves the reduction of operational expenses without having to reduce the quality of services offered. Here again, the insight a digital twin provides can be helpful with reducing waste. An example of this is the use of the digital twin by KONE, an elevator company. KONE makes use of digital twin technology to understand how people move through buildings and the decisions they take when riding an elevator. The knowledge gotten from the use of a digital twin helped the company cut out three to four minutes from the average elevator commute. This, in turn, reduced maintenance cost and increased productivity for building owners.

KONE’s case study highlights the fact that hotel owners can make use of the digital twin and scheduling software to analyze commutes, reception traffic, kitchen and dry cleaning process with the aim of increasing workforce productivity. The model can also be used to enhance customer experience by reducing commute from the reception floor to hotel rooms. As for restaurants, this can be taken further to simplify the drive-through process and increase worker efficiency thereby eliminating waste.

The journey to a smarter hospitality industry also provides the perfect environment for enhancing productivity and providing seamless experiences for customers. Embedded devices and IoT solutions can be used to map out customer attractions and the areas that witness more customer traffic. With this information, simulations run through the digital twin can create optimized schedules for visitation periods. This will ensure that customers do not wait in long queues before being able to access areas of attraction within a facility.

Carving a Niche in the Competitive Hospitality Industry

 Staying afloat in the hospitality industry in order to reap a part of its staggering $550billion revenue requires some effort. These efforts consist of creating an efficient system that takes care of every need of the customer. With advancements in technology, the task of creating that system has become more streamlined and visible to business owners. The digital twin offers visibility and the ability to access real-time information before designing or recreating efficient systems.

CKE Restaurant Holdings, Inc.’s use of Simio’s digital twin solutions provides an excellent case study that highlights how important digital twin is to the transformation of the hospitality industry. With these solutions business owners can better access both small and large scale operational process and enhance these process to the benefit of your customers. You can learn more about the competitive edge the digital twin offers your hospitality and restaurant facilities by speaking to a Simio representative today.

Resources:

https://www.google.com/url?sa=t&source=web&rct=j&url=https://marriott.gcs-web.com/static-files/b82978a6-9d28-4e38-9855-fc4ae2cebe11&ved=2ahUKEwjH8YGxjKPlAhWNTsAKHesCC3EQFjAOegQIBxAB&usg=AOvVaw1wOGkSQxcJ8O7VZBmYm1xF

https://www.nextguestdigital.com/blog/hospitality-digital-tech/

https://www.simio.com/applications/industry-40/Digital-Twin.php

https://www-forbes-com.cdn.ampproject.org/c/s/www.forbes.com/sites/lanabandoim/2019/09/25/how-cke-restaurants-is-using-virtual-reality-to-innovate/amp/

https://www.google.com/url?sa=t&source=web&rct=j&url=https://inbuildingtech.com/uncategorized/digital-twins-proptech/&ved=2ahUKEwi6ieSMjaPlAhWMXsAKHYvxC94QFjACegQIAhAB&usg=AOvVaw2JkDmpLHU5Vs0BI4inPD4n