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Inside a modern manufacturing facility, operations scheduling ensures that all of the production processes are carefully coordinated to ensure an efficient, profitable operation.
Data or the inputs for manufacturing scheduling comes from enterprise resource planning (ERP system), manufacturing execution system (MES system), manufacturing resource planning (MRP system), other native manufacturing systems.
The data takes the form of:
This data is processed and the perfect schedule is generated ... hopefully.
What makes operations scheduling so challenging is that enterprise manufacturing environments have grown incredibly complex. And the reason for this growth in complexity is the consumer's demand for mass customization.
Take automotive manufacturing for example. In the past, a car manufacturer could satisfy consumer demand by producing several different car models in a dozen or so different colors.
But today, consumers want to be able to customize just about every feature of the car ... the wheels, headlights, mirrors, seats, trim, sound system, navigation system, transmission, engine, and the list goes on.
From an operational standpoint, this means that you not only need to have a wide variety of different parts available, but also a highly skilled workforce (both humans and robots) that can assemble vehicles with all of these different features.
And if that wasn't already challenging enough, you need your operations scheduling team to figure out the best order in which to produce these products to:
The operations scheduling teams have to optimize the flow of thousands of pieces of raw material as they are processed by hundreds of robots and workers to build thousands of varieties of the final product. And for the past twenty-five years, even the largest enterprise manufacturers have handled the operations scheduling process manually.
In other words, manufacturing operations managers were limited to using their own brainpower and possibly a scheduling tool like excel to make complex production planning and scheduling decisions.
They were forced to take a heuristic approach and simplify the production environment for this most basic sort of production scheduling in a spreadsheet. The resulting production schedules were nothing but rough estimates. When they were executed in the factories it became clear that a higher level of resolution was needed.
Often entire sections of the shop floor would come to a screeching halt because the following constraints and resources were not accounted for in the plan:
When it comes to the production management of an enterprise manufacturing facility, a few minutes of downtime often costs thousands of dollars. Inefficiency is very expensive.
The reality is that a modern production environment is so complex, often with many different types of manufacturing processes, that schedulers need to consider hundreds of millions of combinations to identify the best production schedule. Unfortunately, the human brain, even when aided by excel, cannot consider more than a thousand possible combinations.
Equally problematic, is the fact that disruption is the norm in the manufacturing ecosystem. Materials are often delayed due to challenges with suppliers, important pieces of equipment can go down, workers may be out, and consumers may make last-minute order changes.
Job schedulers need to make adjustments quickly so that production can continue following significant changes. But even large, dedicated production scheduling teams, can take hours to generate a plan after a major disruption occurs. This is not fast enough.
Finally, optimizing production for the current customer demand is not enough. In order to stay competitive, manufacturers also need to engage in resource capacity planning, to ensure that enough manufacturing resources are going to be available to meet future, forecasted demand. This way scheduling can stay efficient. Resource capacity planning is a critical, forward-looking part of operations scheduling and one that demands not only an accurate appraisal of the current production capabilities but extrapolation using input from sales forecasts and business trends. This process also requires sophisticated planning and scheduling tools and cannot be properly executed in Excel.
What is required for efficient operations scheduling is next-generation Advanced Planning and Scheduling (APS) software. This scheduling tool is powered by powerful optimization algorithms that allow the scheduling team to:
The combination of accuracy and speed ensures that the operation runs efficiently, even in the face of disruption.
To find out more about how Fast Optimization Technology can help you improve your operations scheduling process, please reach out to our team at Optessa for a Complimentary APS Consultation.
