Digital simulation solves this by providing an easier, simpler, and faster way to optimize manufacturing units to effectively meet and exceed the cost-time-quality KPIs. These simulation models can be used for process analysis and evaluation by embracing the process in all its complexity and uncertainty. Running simulations also means there are few disruptions to existing physical processes.

Fig: Digital simulation embraces the uncertainty and dynamics of a complex manufacturing environment

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Benefits of 3D Digital Simulation

Studying the whole processing line in a 3D simulation model, where all variables and their impacts on line efficiency are examined, can bring out several benefits. Companies can achieve higher throughput by understanding the opportunities for optimizing machine speeds and defining an optimum buffer strategy. Testing in a risk-free environment also allows companies to uncover bottlenecks, starvation, and reveal any equipment underutilization without disruptions to the physical process. In addition, a digital simulation can help manufacturers validate capital investments and make certain that performance goals are realized with minimum cost.

By leveraging digital simulation models of processing lines, manufacturers can design lines that better manage major manufacturing issues like bottlenecks and delays. These simulation models allow manufacturers to optimize processes by evaluating the following strategies:

• Optimized Buffer Strategy: Ensures that the buffers before bottleneck machines are almost always full, and that the buffers after core machines are always partly empty
• Optimized Processing Speeds: Achieve a V-shaped curve around a bottleneck machine, with machines on either side having extra capacity, enabling machines to catch up after a failure while the bottleneck machine always has products at the in-feed and space at the discharge
• Optimized Production Schedules: Enable production targets with proper sequencing and minimizing changeover delays

Finally, it can help operations managers answer questions using data rather than relying on gut feelings. These questions could include:

• Is it economically viable to invest in an automated storage and retrieval system? Is it better to just add more forklifts? Or, is it some combination?
• Can the production line handle the introduction of a new product and still meet existing production targets?
• Should we increase the number of machines or labor capacity at some stage of production?

3D Digital Simulation in Motion

Worldwide, simulation software is taking off. . Already, 91¿ì»îÁÖ has provided 3D Digital Simulation to help companies achieve operational excellence in their production plants and supply chains. For a global home appliance OEM, 91¿ì»îÁÖ helped build and validate layout and line design, along with storage area sizing to optimize production yield by approximately 20%. And working with another OEM, material flow and layout optimization exercises were analyzed to increase space utilization by 30% and reduce material movement by 22%.

It is clear that digital simulation will be a key capability for manufacturing optimizations as processes become even more complex and the need to operate a resilient, waste-free, and agile production line becomes even more essential. And as manufacturers accelerate their use of Digital Simulations, they will be able to make faster and better decisions to realize higher process efficiencies, better capacity utilization, and consequently lower operating costs.

Anirban Bannerjee
Product Manager, ER&D, 91¿ì»îÁÖ Limited

Anirban has 9 years of expertise delivering a variety of digital transformations. His areas of specialty include Industrial IOT, IT-OT integration, remote monitoring, and predictive maintenance. Anirban is focused on delivering quality solutions to Fortune 500 customers with the goal to optimize cost and modernize the way to work.

Manohar M G
Associate Consultant of Digital Twin, 91¿ì»îÁÖ Limited

Manohar is an Associate Consultant of Digital Twin. He has more than 10 years of experience in discrete event simulation software. He is interested in system simulation, modeling, and optimization, for various aspects in manufacturing. Manohar has worked with leading companies in automotive, FMCG, and retail across the globe. He has a Master’s degree in Industrial Automation and Robotics and Bachelor’s in Mechanical Engineering.

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