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.

How to Sell the Idea of Digital Twin to Your Manager

The business world as we know it is changing. Never have there been so many emerging technologies, models, and business concepts competing for the attention of the business community. Today, we have cloud computing services, the Internet of Things, Artificial Intelligence, Robotics, Automation, Blockchains, and the Digital Twin providing timely business insights for enterprises. This is why the internet and even physical business entities have hundreds of salesmen and women trooping in and out of your private space. Selling the ‘next best thing’ in technology like pharmaceuticals marketers do, to CTOs, CIOs, and other decision-makers.

 In this whirlwind of changing activities and millions of ads advertising the best technology solutions is Digital Twin technology. For those who know the benefits of the Digital Twin and its ability to enhance every aspect of an enterprise’s operation, the challenge of convincing management to take a chance with it remains. This leaves one with the question of what are the best techniques to sell the idea of integrating Digital Twin technology to the boss? As with most sales challenges, the traditional answer generally involves listing its value-added propositions and outlining the returns to be made investing in the technology.

Although the traditional answer to selling new ideas to management remains efficient, the increased competition among cutting edge tech services means more selling points are needed. Thus, to effectively answer the question ‘how do I sell the idea of Digital Twin technology to management’, here are some new and timely tips to consider.

5 Tips for Selling the Idea of Integrating Digital Twin Technology to Decision-makers

As a sales representative, business development, or system integrator staff/employee who is part of a team, the successful introduction of new technology solutions depends on your approach. This is because you will serve as the driving force behind ensuring the implementation of Digital Twin technology improves the company’s operational processes to deliver optimal services to customers. The tips for selling the idea of Digital Twin Technology include:

Making Your Case with Data – The task of convincing those who control the money and decide what investments are to be made is not for the faint-hearted. You must come prepared and one of the ways to prepare for every question that may come your way is having the required data in place that answers the most important questions. According to a Mckinsey report, integrating data analytics in the right place or in your sales pitch is one way to convince skeptics on the importance of Digital Twin technology. The data to be included must be relevant to the situation or scenario you intend to create when selling Digital Twin Technology. To simplify your search for adequate information, here are some of the data you will need:

  • To answer the question of the adoption rate and how the competition intends to use Digital Twin technology to enhance business operations, the IDC data on adoption can help. The IDC forecasts that 40% of IoT platform vendors and 70% of manufacturers will be making use of Digital Twin technology by 2022.
  • If the question of how digital twin technology can help increase the revenue of the business, data from the Juniper Research can help you answer the question. According to the research, the use of Digital Twin technology has helped enterprises increase their revenue by 25 to 35%. This is due to the ease in which business insights can be gotten from complex processes and the predictive analytical features of Digital Twin technologies.

Armed with this information, your sale pitch will highlight the importance of staying ahead of the competition by integrating Digital Twin technology to simplify complex processes and difficult business decisions. It can also be applied to drive development and predict future scenarios in a wide variety of industries including manufacturing, architecture, construction, technology, engineering, and healthcare industries.

Make Use of Case Study – With your data in place, the next step to convincing decision-makers in your organization is through the provision of confirmable case studies on how Digital Twin technology can help. This is where a little personal effort comes into play if interested in creating personalized case studies for stakeholders to scrutinize. You can find applicable case studies that highlight how Digital Twin technology has been applied and is still been applied by your competitors here:

  • You can find case studies on the application of Digital Twin technology in the aviation industry, automotive industry, manufacturing, healthcare, mining, and engineering at Simio’s resource center. The case studies here are practical examples that can be integrated into your presentation when making your sales pitch.
  • If you are certain a pitch with case studies may not be enough, then more effort is needed from your end. This effort involves the design of a Digital Twin of a phase of your facilities operations to showcase the benefits of a digital model of physical systems where events can be simulated. Many Digital Twin technology providers offer free trials which can be used to accomplish this task. You can make a request for a Simio Demo to quickly kick start the process of designing a Digital Twin.
  • Provide specific answers to your enterprise or the enterprise’s pain points. Once again, although case studies may be customized to show how Digital Twin technology alleviate business challenges, creating a functional model will do more to pass the message across.

So, the second tip here is making use of case studies to address exactly how Digital Twin technology can be used to eliminate specific challenges an enterprise experiences. The efficient use of case studies is one of the quickest ways to get the ball rolling when trying to sell Digital Twin solutions to the decision-makers in your organization.  

Showcase the ROI – It is a well-known fact that one of the most publicized benefits of Digital Twin technology is the returns it offers enterprises who choose to invest in it. Also, your manager, as well as, stakeholders would definitely expect a breakdown of how much the investment will cost and the returns to expect. It is important to have this in mind because, finances are generally the deciding factor that determines if a positive decision will be made.

According to research by High Tech Software Cluster, the threshold for integrating Digital Twin technology for enterprises costs approximately €50, 000 ($55,000). The study goes on to show that to create digital twin solutions for more complex systems may cost approximately €150, 000 or $165,000. As stated earlier, the returns on this investment can be as much as 35% of the total cost needed to create a Digital Twin. In some cases, returns of approximately 50% have also been reported which highlights the financial leverage Digital Twin technology offers enterprises.

As you probably know, approximations are not enough to sway managers and other decision-makers. This means more exact figures that showcase the total cost of owning a Digital Twin of complex process is needed to successfully sell the idea to management. Calculating the total cost of ownership can be done using an estimate calculator. The estimate calculator is capable of calculating the cost of purchasing the necessary hardware, software packages, energy costs, and other costs associated with owning Digital Twin technologies.

It is also important to highlight any supporting technologies that will be needed for data collection if an accurate Digital Twin is to be developed. These technologies may include embedded systems in manufacturing equipment, IoT devices, cloud computing services to scale simulations, and augmented reality devices. These complementary technologies and services may also add to the bottom line of designing a functional Digital Twin environment of complex systems. Thus, using the estimate calculator to highlight the ROI of creating a Digital Twin is one of the major steps that must be taken to convince management about the need for a Digital Twin.

Ask the Right Questions – During strategy sessions, some push backs are expected and this will definitely be the case when selling the idea of a Digital Twin to enhance business operations. This push back should be expected even after using data to answer questions, creating case studies or applicable scenarios, and defining the return on the investment made. When the expected push back occurs, the best way to understand how management thinks and the challenges they foresee is by asking questions. Asking the right questions provides you with the foundation needed to provide the answers needed to convert non-believers into believers.

The questions to ask are varied and should be determined by the level of skepticism shown by particular decision-makers. Some of the questions you must ask to assess the mindset of your superiors include:

  • Do you need more information to make a decision and what information do you need? The purpose of asking this question is to have an idea about what your audience or manager is thinking. Remember that IT managers are notoriously skeptical about new technology therefore, having an understanding of the prejudices management has against Digital Twin technology is important.
  • I know you love the way things are going, but would you be interested in a 6-month trial? If the feedback you get from the manager and decision-makers is negative due to their satisfaction with how things are within the company, this question might help break the ice. Satisfaction with the present condition of things can dampen the enthusiasm for Digital Twin technology. But pushing for a trial could be the turning point that turns ‘no’ into a ‘yes’.
  • If it helps you surpass your personal targets will you try it? It may come as a surprise to you that managers think more about self-preservation than the success of a business. This is one reason why your manager may be resistant to change. Thus, making your questions a bit personal and putting the manager’s self-interest first may be the strategy that gets him/her to experiment with Digital Twin technology.

These questions should be asked without sounding too pushy to your manager and other decision-makers. This is because a pushy attitude could be interpreted as a desperate attempt to make some money for yourself on the side.

Associate the Integration of Digital Twin with Achieving Business Goals – Finally, the ace in your back pocket should be tying the integration of Digital Twin technology to the ideology of the enterprise. This includes highlighting how Digital Twin can be used to realize the business’s mission statement or meet certain key performance index (KPIs). With the answers to the questions asked above, accomplishing this task should be a bit easier than the first steps of selling the idea to management.

Your ability to showcase the benefits of Digital Twin technology and how it meets your company’s culture or KPIs is determined by your knowledge about the transformative powers of the technology. To accomplish this, a lot of research is needed to know more about how this emerging technology can be applied to your business case. Once again, you can turn to the information highlighted in these tips to refine your pitch to resell the idea of integrating Digital Twin technology to your manager. For more information, you can also choose to attend conferences centered around the adoption of Digital Twin technology in your industry.

The Benefits of Digital Twin Technologies is Worth the Extra Effort

Digital Twin technologies create value in diverse ways that can ease the effort expended doing your job. Some of the more important benefits include:

  • Descriptive Values – The ability to visualize the status of an asset in real-time via its Digital Twin is valuable when those assets or facilities are either remote, complex, or dangerous. In plants and other facilities, a Digital Twin makes information easily accessible for interpretation and to make business decisions.
  • Diagnostic and Standardization Value – In facilities where hundreds of variables are involved with production, Digital Twin technology can be used to stabilize these variables, pinpoint the root cause of problems, and leverage analytics to standardize complex systems.
  • Predictive Value – Industry-leading enterprises like General Electric have used Digital Twin technologies to improve efficiency and the output of plants. This was accomplished using a Digital Twin to propose solutions that can lead to customer satisfaction and profitability.

You can learn more about getting started with Digital Twin technology in your facilities, plants, and business by speaking to a Simio engineer today.

Industry 4.0 Revolution: Understanding the Digital Twin and Its Benefits

The world is moving toward an era of more efficient business operations driving by automation. This was one of the key messages of Mitsubishi Hitachi Power Systems CEO, Paul Browning, at the just concluded 2019 CERAWeek held in Houston. Paul Browning, who was the keynote speaker on the ‘digital transformation agenda’, spoke about Mitsubishi’s use of artificial intelligence (AI), machine learning, and digital Twin technologies to create the world’s first autonomous power plant.  He ended his speech by saying ‘Mitsubishi is building the world’s first autonomous power plant capable of self-healing.’

The use of digital transformation technology to eliminate downtime and reduce unplanned shutdowns are just a few of what can be accomplished with Digital Twin technologies. In fact, the ability to virtualize workspaces and complex systems have important roles to play in achieving the smart factory and Industry 4.0 revolution the most industries dream off. This is because no other emerging technology has the potential to bridge the gap between the physical world driven by machines and the virtual world like the Digital Twin. This is why the Digital Twin market is forecasted to be worth approximately $26billion by 2025.

While the numbers highlight the growing acceptance of Digital Twin solutions, many businesses are a bit skeptical about its implementation and benefits. This is why practical case studies are needed to highlight the application of the Digital Twins and how others have benefited from it.

The Most Important Benefits of Digital Twin Technology

Industry 4.0 business model relies on data to automate business processes. The Digital Twin, in turn, creates the perfect environment for collecting data from every aspect of the manufacturing process for analytics and simulation. When data is accurately collected and a Digital Twin is designed, system integrators, data analysts, and other stakeholders can use it to drive business policies and improve decision-making processes. The benefits Industry 4.0 and manufacturers stand to gain from Digital Twins include:

Enhanced Plant Performance – Having the capacity to access and quantify every information produced from a manufacturing process and the shop floor is key to automation. Digital Twin technologies allow manufacturers collect data from the sensors and embedded systems integrated onto a shop floor. The Digital Twin also takes things a step further by replicating physical manufacturing processes and creating a digital environment where these processes can be assessed.

With the necessary data from equipment, machines, material handling, and production cycles in place, manufacturers can develop policies and run simulations to determine how efficient they are. Once determined, the manufacturing policies and regulations can then be applied on the shop floor. This gives large enterprises a cheaper way to access the effects of decisions on productivity levels.

A DHL study on the importance of Digital Twin in enhancing plant performance highlights the use of Digital Twin by Iveco solutions to optimize welding capabilities. The Iveco manufacturing line struggled with constant breakdown of its welding components which delayed production. The cause of these breakdowns were pin-pointed to a lamellar pack which wore out constantly. To enhance performance and reduce downtime, Iveco designed a Digital Twin model of its manufacturing line/

The Digital Twin model helped Iveco understand the different welding concepts and requirements, as well as, their effect on the lamellar pack. Using simulation and machine learning, Iveco developed an optimal welding process that could forecast the probability of component failures in other to reduce them.

Driven Predictive Maintenance –  One of the benefits of designing a Digital Twin of manufacturing shop floors or plants is the opportunity to integrate predictive maintenance into business models. Predictive maintenance involves the prediction of a component or machine failure and the taken of preemptive action to forestall failure. Digital Twin technology has created an environment that drives predictive maintenance across various systems.

Once again, The Mitsubishi Hitachi Power System plant serves as an example where Digital Twin technology can drive the predictive maintenance policy in Industry 4.0. The Digital Twin model created by Mitsubishi gives power plants the ability to monitor sensors and other parameters that determine the plant’s performance levels. On application, the Digital Twin, alongside AI, and machine learning provided insight on the best time to schedule maintenance activities without disrupting production.

The benefits Mitsubishi reaped from its use of Digital Twins include a more efficient way to discover fault components and a maintenance culture that reduced downtime. The autonomous plant was also able to run self-diagnostics and repair stuck valves that affected power generation. Smart facilities can take advantage of the Digital Twin to drive a predictive maintenance culture which will eliminate resource waste and downtime caused by faulty equipment.

Advanced Control of Complex Systems or Processes – Digital Twin ecosystems provide an avenue to control complex systems and processes in ways other traditional technologies can’t. This is because, AI, machine learning, and simulations can be applied to the digital environment thereby allowing enterprises to see farther. Digital Twin takes control process which involves comparing system performances with set standards, discover deviations, and design corrective actions to greater heights. This makes it a great resource for research in Industry 4.0.

An example of how Digital Twins makes advanced control of complex systems possible can be seen from how the U.S. Department of Energy National Energy Technology Laboratory (NETL) deployed Digital Twin solutions. The Digital Twin of the (NETL) plant was used to carry out research on the use of carbon dioxide to power plants as a replacement to the hazardous coal-powered plants currently in use. The Digital Twin also mapped out the plant’s sensor network in other to optimize its use.

The Digital Twin created by the research team served as a virtual testbed for analyzing operational relationships and their effects on power generation. The benefits of Digital Twins, in this case, included a cheaper more effective way to analyze control process phenomena and reduce downtime. Increasing plant reliability and optimizing the use of resources were also singled out as benefits. 

Easing Training and Onboarding Process – The future of Industry 4.0 is being driven by emerging technology solutions such as the industrial internet of things (IIoT), IoT, automated vehicles and equipment. This means to effectively take advantage of the benefits of Industry 4.0 older and new employees must be thought to function in a smart facility. Digital Twins of plant systems and processes provide a virtual environment for employees to learn about operational processes.

In a case study conducted in an automotive facility, employees were taught the repair and assembling process in a virtualized environment and through manuals. At the end of the training employees preferred the option of learning through virtualized environments and retained more information compared to learning from physical manuals. This means the hands-on learning approach driven by Digital Twin technology creates a better environment for learning complex process safely.

Take Advantage of The Benefits of Digital Twins

The combination of Digital Twin technology and cloud computing has made the design, emulation, scheduling, analytics, and simulation services it offers even more affordable to end-users. Small and medium scale businesses can now access Digital Twin solutions to solve complex problems. This means Digital Twin as a Service is slowly but surely becoming an option for enterprises to explore. You can learn more about the Digital Twin opportunities for your business by contacting the experienced engineers at Simio.

Resources:

https://www.ice.org.uk/knowledge-and-resources/case-studies/digital-twins-for-building-flexibility-into-power

https://www.logistics.dhl/content/dam/dhl/global/core/documents/pdf/glo-core-digital-twins-in-logistics.pdf

https://www.bloomberg.com/news/articles/2018-04-09/forget-cars-mitsubishi-hitachi-sees-autonomous-power-plants

Digital Twin Technology: 5 Challenges Businesses Face By Overlooking It

A Disruptive technology is a product, concept or service that has the ability to redefine the traditional way of doing things.  Today, the digital twin concept is being hailed as a disruptive technology with the capacity to change how we design, solve complex problems and collaborate. In fact, a Gartner Report predicted that by 2021 approximately 50% of industrial companies will integrate the use of digital twin technologies to increase workforce performance and manufacturing efficiency. So, what is this disruptive technological concept?

The Digital Twin refers to a real-time replica of a physical entity. This entity could be a living thing, an inanimate physical object, as well as, assets, processes and systems that function in the physical world or environment. Although this concept is actually three decades old, the convergence of emerging technologies such as the internet of things (IoT), artificial intelligence (AI), machine learning has taken it to new heights. Digital twins juxtapose these emerging technologies to create digital models of physical entities with the ability to simulate real-time changes that occur to the physical model.

An example of how this concept work involve the development of the digital twin of an aircraft. With the digital twin, finite element analysis (FEA) can be applied to determine the fatigue limit of the aircraft’s structure. The results of this simulation can then be used to design or choose more suitable materials or design for a more durable aircraft. Outside manufacturing, digital twins can be employed in diverse industries including healthcare to simulate how the human body reacts to external forces. The benefits of integrating digital twins include increased design efficiency, enhancing predictive analysis, and collaboration.  This is why the market for it is expected to hit approximately $15billion by 2023. The benefits of digital twins are huge but the challenges business will face not embracing it is even bigger.

This article will discuss:

  • The challenges businesses face not integrating the digital twin in business operations.
  • The effects of not embracing the digital twin.
  • The disruptive capabilities of the digital twin.

The Five Challenges Businesses Face Not Embracing Digital Twins

With approximately 50% of industrial companies integrating the use of digital twins, the 50% who don’t will definitely be losing their competitive edge. This is because the digital twin will redefine real-time simulation applications in ways the average 3D modelling software or Building Information Modelling platform can’t aspire to. The challenges to expect include:

Keeping Legacy Solutions, Designs or Data – As the generation of baby boomers continue to retire daily, the probability of losing the knowledge that built legacy equipment and systems could be lost. This includes the Mylar copies of traditional manufacturing equipment or the designs of legacy military aircraft. Regardless of technological advancements, the loss of legacy data destroys the foundations newer prototypes were built on.

With the aid of the digital twin concept, businesses across every industry, can create an accurate digital model of legacy equipment or solutions. The digital model can then be stored for posterity sake or analyzed with the aim of developing upgraded prototypes. Models can also be used as materials for training the younger generation of workers through virtual reality environments.

 Enhancing Lean Manufacturing Processes – Toyota’s integration of lean manufacturing to speed up production while efficiently using resources has become folklore in the automotive industry. The integration of lean manufacturing models – which were disruptive at that time – helped Toyota dominate the industry for decades. This is the leverage the digital twin concept offers. The ability to optimize entire product value chains is something that can be achieved in real-time through the digital twin.

A study at the Bayreuth University, Germany focused on analyzing the impact of digital twins in collecting real-time data and optimizing production systems. The study compared the efficiency of digital twins and the commonly used value stream mapping solutions. In the end, the results showed that digital twins exceeded traditional solutions in data acquisition, automated derivation of optimization measures, and the capturing of motion data. These data which are crucial to optimizing production could also be utilized in a digital twin environment to optimize diverse processes. Thus, shunning digital twins will leave firms in the lurch while competitors who leverage this concept can optimize production variables in real-time.

Limitations in the Integration and Use of Data – The Industry 4.0 revolution currently going on relies heavily on the collection and use of data to receive important business insight and automate processes. The tools or applications currently used today are enterprise relationship management software, and industrial cloud solutions. Although these solutions do excellently well in collecting data from smart or industrial internet of things (IIoT) devices, they still struggle with collecting data from legacy or dumb equipment. This limits the penetration of Industry 4.0 in the deepest layers of manufacturing shop floors which is what the OPC Foundation intends to solve.

Digital twin concepts can help smart factories integrate dumb equipment from the deepest levels of a shop floor into models of the manufacturing plant. This makes it possible to capture the hundreds of non-measured information in the shop floor into a digital environment thereby truly meeting Industry 4.0 and OPC UA standards. If successfully done, the digital twin with the captured data can be used to predict the facilities transient response to external disturbances, equipment failure, and system malfunctions.

Manufacturers who overlook digital twin concepts will be stuck with using data from only smart equipment and IoT devices to track real-time changes on the shop floor. The limitations associated with not capturing non-measured data will lead to approximations when automating operations in a smart factory. This could lead to downtime, an inefficient workforce, and in extreme situations accidents to workers.

Limiting the Effectiveness of Predictive Analysis – Another important challenge shunning the integration of digital twins into industrial operations is the difficulties that come with making blind or half-informed changes. Making blind changes when making important decisions such as designing a new material handling system or reducing the number of processes needed to develop a product will have terrible consequences. These consequences will include wastage of resources, a subpar end product or confusion on the shop floor.

According to Gartner, downtime in the manufacturing industry could lead to huge losses. In the automotive industry alone, downtime is responsible for a loss of $22,000 per minute. Although the numbers may be less in other industries, the effects are still considerable. Digital twins can help eliminate these challenges or losses by helping businesses simulate the real-time effect of making certain changes. For example, a change of production schedule while going through a transition period would have left the aviation manufacturer Lockheed Martin unable to meet its delivery timelines. With the aid of the Simio simulation software, the manufacturer was able to make informed decisions that optimized the production process.

Next Steps

The match to industry 4.0 and a more connected factory is one that must be planned for if manufacturers intend to remain competitive for the long run. One way to achieve this is by integrating a digital twin for simulating and receiving the insights needed to automate industrial processes. If properly executed, you will be turning the disruptive nature of the digital twin to your benefit.

Resources:

https://www.gartner.com/smarterwithgartner/prepare-for-the-impact-of-digital-twins/

https://news.thomasnet.com/companystory/downtime-costs-auto-industry-22k-minute-survey-481017

https://www.isw.uni-stuttgart.de/en/institute/highlights/digital-twin/

https://blogs.opentext.com/addressing-the-data-challenges-in-the-digital-twin/

https://www.gartner.com/smarterwithgartner/prepare-for-the-impact-of-digital-twins/

The Evolution of the Industrial Ages: Industry 1.0 to 4.0

The modern industry has seen great advances since its earliest iteration at the beginning of the industrial revolution in the 18th century. For centuries, most of the goods including weapons, tools, food, clothing and housing, were manufactured by hand or by using work animals. This changed in the end of the 18th century with the introduction of manufacturing processes. The progress from Industry 1.0 was then rapid uphill climb leading up to to the upcoming industrial era – Industry 4.0. Here we discuss the overview of this evolution.

Industry 1.0 The late 18th century introduced mechanical production facilities to the world. Water and steam powered machines were developed to help workers in the mass production of goods. The first weaving loom was introduced in 1784. With the increase in production efficiency and scale, small businesses grew from serving a limited number of customers to large organizations with owners, manager and employees serving a larger number. Industry 1.0 can also be deemed as the beginning of the industry culture which focused equally on quality, efficiency and scale.

Industry 2.0 The beginning of 20th century marked the start of the second industrial revolution – Industry 2.0. The main contributor to this revolution was the development of machines running on electrical energy. Electrical energy was already being used as a primary source of power. Electrical ma- chines were more efficient to operate and maintain, both in terms of cost and effort unlike the water and steam based machines which were comparatively inefficient and resource hungry. The first assembly line was also built during this era, further streamlining the process of mass production. Mass production of goods using assembly line became a standard practice.

This era also saw the evolution of the industry culture introduced in Industry 1.0 into management program to enhance the efficiency of manufacturing facilities. Various production management techniques such as division of labor, just-in-time manufacturing and lean manufacturing principles refined the underlying processes leading to improved quality and output. American mechanical engineer Fredrick Taylor introduced the study of approached to optimize worker, workplace techniques and optimal allocation of resources.

Industry 3.0 The next industrial revolution resulting in Industry 3.0 was brought about and spurred by the advances in the electronics industry in the last few decades of the 20th century. The invention and manufacturing of a variety electronic devices including transistor and integrated circuits auto- mated the machines substantially which resulted in reduced effort ,increased speed, greater accuracy and even complete replacement of the human agent in some cases. Programmable Logic Controller (PLC), which was first built in 1960s was one of the landmark invention that signified automation using electronics. The integration of electronics hardware into the manufacturing systems also created a requirement of software systems to enable these electronic devices, consequentially fueling the software development market as well. Apart from controlling the hardware, the software systems also enabled many management processes such as enterprise resource planning, inventory management, shipping logistics, product flow scheduling and tracking throughout the factory. The entire industry was further automated using electronics and IT. The automation processes and software systems have continuously evolved with the advances in the electronics and IT industry since then. The pressure to further reduce costs forced many manufacturers to move to low-cost countries. The dispersion of geographical location of manufacturing led to the formation of the concept of Supply Chain Management.

Industry 4.0 The boom in the Internet and telecommunication industry in the 1990’s revolutionized the way we connected and exchanged information. It also resulted in paradigm changes in the manufacturing industry and traditional production operations merging the boundaries of the physical and the virtual world. Cyber Physical Systems (CPSs) have further blurred this boundary resulting in numerous rapid technological disruptions in the industry. CPSs allow the machines to communicate more intelligently with each other with almost no physical or geographical barriers.

The Industry 4.0 using Cyber Physical Systems to share, analyze and guide intelligent actions for various processes in the industry to make the machines smarter. These smart machines can continuously monitor,detect and predict faults to suggest preventive measures and remedial action. This allows better preparedness and lower downtime for industries. The same dynamic approach can be translated to other aspects in the industry such as logistics, production scheduling, optimization of throughput times, quality control, capacity utilization and efficiency boosting. CPPs also allow an industry to be completely virtually visualized, monitored and managed from a remote location and thus adding a new dimension to the manufacturing process. It puts machines,people, processes and infrastructure into a single networked loop making the overall management highly efficient.

As the technology-cost curve becomes steeper everyday, more and more rapid technology disruptions will emerge at even lower costs and revolutionize the industrial ecosystem. Industry 4.0 is still at a nascent stage and the industries are still in the transition state of adoption of the new systems.Industries must adopt the new systems as fast as possible to stay relevant and profitable. Industry 4.0 is here and it is here to stay, at least for the next decade.

Optimizing the Smart Factory

In the same way that a product development involves prototyping, the production process for manufacturing that product should also be optimized for maximum efficiency and productivity.Discrete Event Simulation (DES) software approximates the manufacturing process into individual events, so can be used to model each step in manufacturing process for overall performance optimization.

The IT innovations of Industry 4.0 allow data collected from its digitalized component systems in the Smart factory to be used to simulate the whole production line using Discrete Event Simulation software.

Real time information on inventory levels, component histories, transport, logistics and much more can be fed into the model, developing different plans and schedules through simulation. In this way, alternative sources of supply or production deviations can be evaluated against each other while minimizing potential loss and disruption.

When change happens, be it a simple stock out or equipment breakdown or an unexpected natural disaster on a huge scale, Discrete Event Simulation software can produce models showing how downstream services will be affected and the impact on production. Revised courses of action can then be assessed and a solution implemented.

The benefits of using Discrete Event Simulation software to schedule and reduce risk in an Industry 4.0 environment include assuring consistent production where costs are controlled and quality is maintained under any set of circumstances.

Scheduling in the Industry 4.0

Today started badly.

As soon as I hopped into my car, the GPS system was flashing red to show queues of stationary traffic on my regular route to the office. Thankfully, the alternative offered allowed me to arrive on time and keep my scheduled appointments.

In the same way as a GPS combines live traffic data with an accurate map of the city, Simio Software connects real time data sources with a modeled production situation. Just like a GPS, Simio can also impose rules, make decisions, schedule and reschedule.

The major difference is in the scale.

Simio Simulation and Scheduling Software can model entire factories, holding huge quantities of detailed data about each resource, component and material. It leverages big data analysis to run thousands of permutations of scenarios, finding the optimum outcomes for specific circumstances. Lightning fast, it can detect and respond to changes with suggestions that will keep everything flowing in the best possible way.

Thank goodness for Simio, because Industry 4.0 is here.

Smart Factories employ fully integrated and connected equipment and people, each providing real time feedback about their state. Data is constantly collected on each product component, for process monitoring and control. Every aspect of the entire operation is managed through its associated specifications and status data. This large, constant stream of information coming from a known factory configuration can be received, stored, processed and reported upon by the powerful Simio software.

With Industry 4.0, nothing is left to chance. Everything is monitored and optimized, and performance is predicted, measured, improved and adapted on an ongoing basis. Management of so many interconnected components requires a scheduling system that is specifically designed to operate in this dynamic data environment. Simio Production Scheduling Software can be relied upon to provide the integrated solution for enabling technology in the Smart Factories of the future.

We are already seeing a rise in robotics and the increasing digitalization of the manufacturing industry under the effects of Industry 4.0. Soon all components of the factory model will be interconnected, just like my future driverless car that will communicate directly with my GPS to take the best route using current traffic information.

All I will have to do is sit back and enjoy the ride.