The Production Scheduling Maturity Model
From the spreadsheet to APS and, ultimately, to OPS
Most manufacturers employ large, unwieldy Excel spreadsheets to perform production scheduling. These spreadsheets are developed by experienced – and very skilled – production planners, who have attempted to pour all their knowledge into the spreadsheet. Soon, these spreadsheets have become so complex and error-prone that they are a pain to maintain, and nobody else can understand them, nor use them effectively.
The company, realizing they need a system that is easier to maintain and to use, begins looking for a quick solution, either as a module included in their current ERP system, or as some off-the-shelf software product. These products use an approach commonly known as Advanced Planning and Scheduling (APS), which offer fancy drag-and-drop capabilities and other bells and whistles for the user. However, If their production process is complex, companies soon realize a quick solution does not exist. These ERP modules or COTS products usually require so much customization that the price tag becomes prohibitive and the effort impractical.
APS usually uses a set of business rules (often called “dispatch rules” or “heuristics”) to schedule production. While these rules can be customized to a particular type of manufacturing operation or even to certain specific situations encountered during production, the approach is quite rigid, often leading to suboptimal schedules.
Optimal production scheduling (OPS) uses true mathematical optimization algorithms to maximize efficiency and minimize costs in production processes. OPS determines the best way to allocate resources and schedule production activities based on factors such as available capacity, customer demand, and production costs.
While both OPS and APS are useful tools for improving production efficiency, optimal production scheduling is generally considered to be more effective. This is because OPS takes a more holistic approach to production planning, considering a wide range of factors and constraints while optimizing for multiple objectives, such as minimizing production costs, maximizing capacity utilization, and maximizing throughput.
OPS is also easy to re-configure under dynamic conditions in the shop floor. In the event of a disruption (such as a machine breaking down, or the absence of a key operator), OPS just needs the updated data, while APS must be “re-trained.”
BBA offers the most advanced true optimization algorithms that are appropriate for each manufacturing operation. Our production scheduling engine is easy to integrate with current ERP or MES systems, creating an end-to-end optimal scheduling solution for the most complex production processes.
Visit us at www.bettersolv.com to learn more about what BBA can do for you.