Why More Manufacturers are betting on Simulation Software in 2020

In the past decade, the manufacturing industry struggled to increase its production rate even with the implementation of lean manufacturing concepts within shop floors. A major cause of the stagnant productivity levels manufacturers’ encountered was strategy planning and its implementation. In many cases, the inability to accurately assess how strategic changes affect production led to downtime, resource waste, and an increase in expenditure. This is where simulation software as an advanced planning tool helps.

Statistics from 2018 showed that approximately 60,000 manufacturing enterprises worldwide made use of simulation as a planning and scheduling tool. The reason for the low adoption rates was because most enterprises see simulation as a fad which may not work as expected when assessing business strategies. For others, the tried and tested traditional planning tools such as excel and intuition is more than enough when developing business strategies. This left the task of sensitizing the manufacturing industry in the hands of simulation software vendors.

By 2020, the number of manufacturing enterprises using simulation had increased to 110,000 which highlights the efforts vendors such as Simio have put into simplifying simulation for everyone. Progress in the development and features of simulation software is also playing a part in convincing manufacturing enterprises to consider simulation software as planning tools. An example is the addition of 3D modeling and animation into simulation platforms which provides more detailed visuals which explain KPI’s better.

The growing reliance on simulation as a planning and scheduling tool is due to the benefits it offers both discrete and continuous manufacturing facilities. These benefits include enhancing risk analysis procedures, forward scheduling, and effective monitoring of existing systems. Below is a holistic view of these advantages simulation offers.

Risk Analysis with Simulation Software

Risk analysis is the process of identifying and analyzing potential challenges that could negatively affect the manufacturing process and an enterprise’s ability to meet production timelines. Once the limiting factors or issues have been identified through risk analysis, decisions to mitigate them can then be taken.

Simulation software is an excellent tool for risk analysis within manufacturing facilities and operations. With simulation, a manufacturer can determine if available resources such as an inventory list, number of equipment, and workstations are enough to meet production schedules. An example is conducting a risk analysis to determine the probability of meeting an order with the resources available to the manufacturer.

In this instance, Simio is used to conduct a risk assessment which will provide the risk percentage attached to supplying the requested order. Risk percentage refers to on-time probability for an order with considerations for the number of replications run using the simulation software. We recommend running at least 10 replications to determine the risk percentage. This is because it provides a more accurate risk analysis for producing the order within the specified time frame. You can learn more about risk assessment with Simio here.

If the result for the ‘risk measures’ after running a risk analysis is within the 80 to 90% mark, this is a good sign that the order will be fulfilled on-time. A risk measure of less than 30% is a sign that more resources are needed to ensure an order is produced on-time. The manufacturer can then choose to make design or operational changes to ensure production is on-time. Here, a design change could mean adding an extra assembly line or purchasing more material handling equipment to speed up operations. Operational changes refer to expediting a material or working to extend the due date of the requested order.

Making these decisions reduce the challenges that affect manufacturing procedures such as downtime, resource waste, and overshooting production timelines. Eliminating these challenges or keeping them at bay comes with its benefits which include revenue growth and enhancing customer experience.

Forward Scheduling with Simulation Software

In advanced planning, forward scheduling refers to a feasibility analysis of manufacturing plans before implementation. This allows the schedule to take into consideration all known constraints and condition of a system that could affect production, unlike backward scheduling which makes assumptions without considering some important constraints.

The application of forward scheduling in manufacturing provides enterprises with a valuable tool to make plans with the resources currently available, as well as, plan for the future. An example is scheduling the production of an order of 100 items. Forward scheduling will consider the available inventory and its ability to support the order. If the available materials are not enough, this constraint is taking into consideration and the system sends out a purchase order for more supplies. In a situation where the start date has elapsed or the demand exceeds the manufacturer’s capacity, forward scheduling continues to create schedule past the due date.

This information gives stakeholders options. The decision to be made here may involve trying to push the due date forward or outsourcing a percentage of the order if the delivery date cannot be changed.

Planning before Implementation with Simulation

Simulation software is a virtualization tool built for planning factory layouts or settings to enhance productivity. Manufacturers intending to build new facilities or add new workstation or production lines to existing facilities can predict their impact before executing the implementation procedure.

An example is assessing the impact of adding an assembly line to a discrete manufacturing facility. With Simio, a discrete event simulation assesses the speed of the new system and the scheduling probabilities it offers. This assessment provides a glimpse into the future manufacturing system and if the prognosis looks good for optimizing productivity, then real-time implementation comes next.

Assessment before implementation also applies to planning new shop floor layouts that optimize available manufacturing assets and workspace. An agent-based simulation highlights the effects or impact of individual assets to the entire facility. With this information, an enterprise can place assets in specific sections while modeling the entire facility to take advantage of the location of assets. On implementation, a properly planned shop floor layout reduces workplace traffic, speeds up production activities, and optimizes available resources.

Conclusion

The value-added proposition simulation brings to the table is why manufacturers are expected to spend approximately $2.5billion annually on simulation software. Simulation software is used by machinery and appliance facilities, the automobile industry, in aviation, healthcare and any other industry where goods are produced or services are rendered. You can learn more about how simulation software has been applied to simplify manufacturing processes within your industry by going through the list of Simio case studies.