In 2019, an industrial facility struggled with optimizing its schedules, maximizing resources, and cutting down on astronomical production costs due to the complex nature of its manufacturing process. The facility relied on a high-mix and low-volume manufacturing process with sequence-dependent setup times which added an extra level of complexity to its manufacturing processes.
To eliminate its struggles with developing an optimized schedule and to properly manage resources, the use of deterministic scheduling was explored but deterministic scheduling was unable to create accurate schedules, capture variabilities nor account for the event uncertainties that occurred within the factory floor. To solve this complex scheduling problem, the manufacturer turned to Simulation modeling to develop risk-based schedules that accounted for the multiple variables and uncertainties within the factory’s floor. The resulting schedules resulted in optimized resources and a reduction in operational cost.
Simulation and risk-based scheduling is the dual use of a simulation model or Digital Twin to generate detailed retail-constrained schedules and probability-based risk analysis that account for variations within a manufacturing system. Today, industrial facilities that choose to reduce risk and optimize scheduling processes have integrated diverse industry 4.0 technologies to capture factory floor data but data capturing tools simply capture data and analytical tools are needed to optimize specific processes. Simulation modeling and risk-based scheduling is a powerful tool to improve overall productivity.
Like the example above, facilities that integrate industry 4.0 will leverage the digital twin and simulation modeling to accomplish diverse tasks which range from real-time monitoring to risk-based scheduling to create straight lines where complex and tangled processes exist.
Why Do Factories Need Simulation and Risk-based Scheduling?
Brownfield facilities dealing with complex manufacturing processes such as multiple production variables and event uncertainties rely on the rule of thumb to ensure production lines function as best as they can. In most cases, the reliance of traditional knowledge horned by years of practice does little to simplify complex processes or to bring order to poorly-drawn schedules. The inefficiencies within Brownfield facilities led to Industry 4.0 and the data-driven optimization policies it promises.
Brownfield facilities require simulation modeling and risk-based scheduling to reduce the workload of shop floor operators, optimize resource allocation, and drastically reduce labor cost. For Brownfield facility owners the process of taking advantage of risk-based scheduling starts with digitalization and collecting the needed data simulation software required to develop accurate risk-based schedules.
Greenfield facilities also require simulation and risk-based scheduling to get the best out of implemented industry 4.0 initiatives and captured data. Unlike Brownfield facilities, the large data capturing capabilities of the IIoT and edge applications within more modern facilities provide the data needed to develop accurate simulation models for risk-based scheduling.
With risk-based scheduling, Greenfield facilities gain up-front visibility into every inherent risk associated with a schedule or production plan. Thus, providing the needed information to make accurate decisions without losing resources in real-time.
Register for Our Free Webinar To Learn from The Experts
The best way to analyze the benefits of simulation and risk-based scheduling to the industrial sector is through real-world practical examples that relate to your facility’s operations. On the 4th of February, Simio will be hosting Tolga Yanasik of Dijitalis in a free webinar discussing why your facility needs simulation and risk-based scheduling using applicable use-cases. You can register to participate in the free webinar here.