If we visualize the various supply planning solutions as a pyramid model, detailed scheduling is at the lowest level, followed by master planning, Rough-Cut Capacity Planning (RCCP), budget planning and strategic planning in ascending order. Detailed scheduling is at the top in terms of complexity, however, because the closer you are to the production date, the less aggregation is permitted. Even today, many organizations still build their detailed schedule in Excel. Excel is great as a spreadsheet application, but it was never designed to be used for detailed scheduling. The framework of a detailed scheduling tool, such as Arkieva, can help planners to develop a structured way of creating a detailed schedule. In essence, a detailed scheduling solution takes five building blocks into account: jobs, machines, constraints, objectives and solution methods.
Jobs define the individual steps in the production process towards a finished product. A job can thereby consist of a single operation or a collection of operations. Jobs also involve several characteristics, such as the processing time, starting and completion time, priority factor and precedence relationship.
Scheduling is about jobs which need to be put on machines. A single machine or a collection of machines can have a certain sequence or routes. In a ‘flow shop’ environment the routes of all jobs are identical, whereas in a ‘job shop’ environment the jobs have different routes or even recirculate, like in the semiconductor industry. The more different routes and recirculation, the more complex your scheduling will be.
Although scheduling may seem easy, it has to take into account many practical constraints like the unavailability of raw materials or packaging, limited manpower to execute specific activities such as changeovers, the fact that not every job can be done on every machine, limited storage space, unexpected orders rushed through pushed Sales which disrupt the normal flow of operations, etc. Due to the continuous and short-term nature (daily updates in a 3 to 12-day horizon), a scheduler’s job is never finished.
Every organization would like to optimize on all fronts at the same time, but it’s unrealistic to do so. Therefore, organizations have to prioritize their objectives. What’s more important: to deliver on time and realize the Service Level Agreements (SLAs) or to hold less inventory? Or, if there’s a capacity constraint, maybe the optimization of the changeover time should be the top priority? Of course, if there’s slack, it’s certainly possible to focus on several objectives simultaneously, but it’s wise to start scheduling with the first objective in mind. By visualizing the optimization objectives – throughput, cycle time, tardiness, set-up costs, etc. – planners can make the right decisions more quickly and more easily. The what-if scenario functionality of detailed scheduling solutions can also be very helpful: if I increase my focus on the on-time delivery, how will that impact on my inventory, and vice versa?
5. Solution methods
Other solution methods will be needed depending on your level of complexity. For simple problems, there are ‘known’ and ‘optimal’ solutions: techniques like the Earliest Due Date First or the Critical Path Method. However, complex problems may have no ‘optimal’ or no ‘known’ solutions. In that case you can resort to heuristics. This means that the scheduling tool proposes a good solution with an approximation of the minimum/maximum performance against the objective in a reasonable amount of time.
In short, scheduling is all about taking the result of the Material Resource Planning (MRP) and translating it into a schedule of jobs on specific machines within certain constraints while trying to maximize performance against certain objectives. Ultimately, the schedule will generate shop floor orders that trigger the Manufacturing Execution System (MES) or the Enterprise Resource Planning (ERP) system. These systems directly steer the operations on the shop floor.
You should choose your solution methods in line with the complexity. Excel can be fine if your operations aren’t too complex, but even then you’re missing out on the many benefits and savings that scheduling software can offer. If the pressure on the objectives or constraints increases, you will be forced to search for a more professional solution which can structure data in a way that makes it possible to maintain an overview. These five building blocks are a good starting point for discovering which solution is best suited to you. The more complex your situation is in the four first steps, the more advanced your solution will need to be.
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