Simulation Modeling in Production

When I was working with one of my customers—an automotive manufacturer—we were about to launch a new assembly line for a critical product. Everything was planned down to the last detail, and they felt confident. But here’s what I told them: “𝘓𝘦𝘵’𝘴 𝘳𝘶𝘯 𝘢 𝘋𝘪𝘴𝘤𝘳𝘦𝘵𝘦 𝘌𝘷𝘦𝘯𝘵 𝘚𝘪𝘮𝘶𝘭𝘢𝘵𝘪𝘰𝘯 𝘧𝘪𝘳𝘴𝘵, 𝘫𝘶𝘴𝘵 𝘵𝘰 𝘣𝘦 𝘴𝘶𝘳𝘦.” At first, they didn’t see the need. After all, they had invested in top-tier equipment, trained the team, and scheduled everything perfectly. But I insisted, knowing the potential risks. 𝗔𝗻𝗱 𝘁𝗵𝗮𝗻𝗸 𝗴𝗼𝗼𝗱𝗻𝗲𝘀𝘀 𝘄𝗲 𝗱𝗶𝗱. During the simulation, we discovered a potential bottleneck in a key station. Operators were expected to handle more than they realistically could, and the result? Significant downtime and production delays if left unchecked. → Without DES, they would’ve found out the hard way—after launch. → 𝗪𝗶𝘁𝗵 𝗗𝗘𝗦, we identified the issue in hours and adjusted the process before a single part hit the line. Here’s exactly how we did it: We mapped out the entire process in a simulation environment. We tested multiple production scenarios, including different demand levels and equipment breakdowns. We identified where the bottlenecks would occur and adjusted the line accordingly. We optimized the workflow, balancing the load across stations, ensuring smooth operations. The result? They launched the assembly line 𝗼𝗻 𝘁𝗶𝗺𝗲, avoided costly downtime, and avoided over $100K in potential rework and delays and and prevented future costs that would have compounded over time. 𝗧𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗽𝗼𝘄𝗲𝗿 𝗼𝗳 𝗗𝗶𝘀𝗰𝗿𝗲𝘁𝗲 𝗘𝘃𝗲𝗻𝘁 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻. If we hadn’t run the simulation, they would have lost weeks of production time fixing a problem they never saw coming. So, if you’re setting up a new assembly line, ask yourself: → Are you willing to risk delays and unexpected costs? Or would you prefer to 𝙞𝙙𝙚𝙣𝙩𝙞𝙛𝙮 𝙖𝙣𝙙 𝙨𝙤𝙡𝙫𝙚 𝙥𝙤𝙩𝙚𝙣𝙩𝙞𝙖𝙡 𝙥𝙧𝙤𝙗𝙡𝙚𝙢𝙨 𝙗𝙚𝙛𝙤𝙧𝙚 𝙩𝙝𝙚𝙮 𝙝𝙖𝙥𝙥𝙚𝙣? This is how modern manufacturing leaders avoid the pitfalls that kill efficiency. 𝙄𝙛 𝙮𝙤𝙪’𝙧𝙚 𝙧𝙚𝙖𝙙𝙮 𝙩𝙤 𝙨𝙚𝙚 𝙝𝙤𝙬 𝘿𝙀𝙎 𝙘𝙖𝙣 𝙨𝙖𝙛𝙚𝙜𝙪𝙖𝙧𝙙 𝙮𝙤𝙪𝙧 𝙤𝙥𝙚𝙧𝙖𝙩𝙞𝙤𝙣𝙨, 𝙡𝙚𝙩’𝙨 𝙩𝙖𝙡𝙠. 😊 → DM me, and I’ll help you implement the same strategy that worked for my customer. It’s practical, it’s effective, and it’s what separates the good from the great.

Analysis of Production Lines by Simple, Fast and Scientific Simulation: Apparently, there is no powerful tool in Lean, TOC, Six Sigma, ERP/MRP, Industry 4.0, Generative AI, etc. for simple, easy, quick and sensible analysis of dynamic nature of production lines which are influenced by numerous factors like average cycle time, variation in cycle time, number of resources available, resource calendars, resource speeds, failures and repairs of resources, rework/rejections, etc. Factory Physics / Operations Science is helpful to some extent in this regard but it is not adequately flexible. In my opinion, discrete event simulation (DES) is a powerful, unique method for thorough analysis of dynamic nature of production lines and the effects of those factors. DES is however largely ignored in production systems even by engineers and managers who have a course on DES in college. DES is usually done in industries by simulation experts using sophisticated simulation packages. DES is still considered as fancy or alien by many factory people and consultants. I would emphatically say that DES can be run for production lines easily, quickly, effortlessly and sensibly using simple, scientific software tools like FlowshopSim which are created exclusively for simulating production lines at a high speed. This DES does not require formal simulation knowledge at all. However, I would not recommend watching time-consuming animation in simulation. For analysis purpose, I would look into output summary and the trace of simulation available in graphical and tabular forms. If any engineer/manager or a Lean consultant wants to witness such production line simulation, I would be happy to run FlowshopSim over web for any specified scenarios of a production line. DES in FlowshopSim will not take more data, time and effort than VSM. It quickly provides a lot of knowledge about the production line to be simulated and is far more effective than #vsm for finding bottlenecks and improvement opportunities on the line. Moreover, it facilitates fast, extensive and reliable what-if analysis of the system. What-if analysis of a stochastic production system is absent in all other methodologies for manufacturing systems. The simple and powerful FlowshopSim leverages the knowledge and experience I gained in simulation and scheduling over more than 40 years (after my PhD) as a researcher, academician and manufacturing consultant. Two days ago, I demonstrated over web simulation of various scenarios of a production line to a senior manufacturing consultant Jean-Pierre Goulet, P. Eng., M. Sc. A. in details for more than an hour. I believe he noticed its power, speed, versatility and simplicity for simulating production lines. Intelligent analysis of a system can make continuous improvement drive more efficient. Let us look for improvement in tools and methodologies also. #factorysimulation #productionline #lean #flow #continousimprovement

Explore how the Siemens Electronics Factory Erlangen (GWE) combines Digital Twins, simulations, and real production data to analyze countless scenarios and optimize material flows, reduce energy consumption, boost productivity. Combining simulations and real data, they enhance material flows, cut energy consumption, and boost productivity. The result: 40% reduced material circulation, 10% improved AGV accuracy, and a 70% decrease in ventilation energy use. https://sie.ag/7SSFF