The evolution and future of Advanced Planning Systems (APS)
Jawad Khan Niazi
?? Customer Success Champion | ?? SaaS Growth Hacker | ?? Business AI Evangelist
Photo by ThisisEngineering RAEng on Unsplash
Prototypes are easy, production is hard.
Elon Musk
?In this blog post, we will look into a type of industrial software systems known as Advanced Planning and Scheduling softwares, how they evolved, what does SAP offer in this software category and what does the future look like.
First let’s look at the definition of Advanced planning and Scheduling (APS).
Advanced planning and scheduling (APS, also known as advanced manufacturing) refers to a manufacturing management process by which raw materials and production capacity are optimally allocated to meet demand. APS is especially well-suited to environments where simpler planning methods cannot adequately address complex trade-offs between competing priorities.
Wikipedia (https://en.wikipedia.org/wiki/Advanced_planning_and_scheduling)
The evolution of APS systems started with the era before MRP (Material requirements Planning) with simpler inventory management methodologies like reorder point planning and economic order quantity governed the production process. MRP aimed to co-ordinate the various departments in the company to organize manufacturing resources, ensure raw material is available for production and finished material is available to serve customer orders. A good MRP system aimed to solve material shortages, keep optimum work in capital and generate a production schedule. The MRP approach often assumed infinite resource capacity and was not equipped to handle constraints in manufacturing. Later on, capacity was considered and the new paradigm came to be known as MRP II (Manufacturing Resources Planning).
The next step in this evolution was the birth of the first ERP systems where Software companies like SAP led the charge and aimed to create software that integrated all departments under a single source of truth to create the ultimate system of record. ERP systems by definition increased the scope beyond manufacturing to include other lines of business such as marketing, finance and HR.
The immense popularity of a single system of truth for the whole organization resulted in exponential adoption of ERP globally and ultimately led to the emergence of specialized applications for different lines of businesses to extend the ERP system.
When MRP II was no longer enough to cater to the business requirements because it required a stepwise procedure to plan material and capacity separately, was difficult to create adaptive production plans that considered volatility (in demand, resource capacity and material availability) - Advanced Planning and scheduling systems filled the gap with simultaneous planning and scheduling of production based on available resources (material, labor and machine). Most APS systems also allow visualization of the planning results and simulation capabilities.
Advanced Planning systems use complex mathematical algorithms to forecast demand, to plan and schedule production within specified constraints, and to derive optimal source and product-mix solutions.
Vieira, J., Deschamps, F., & Valle, P. D. (2021). Advanced Planning and Scheduling (APS) Systems: A Systematic Literature Review.
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How to APS systems solve planning problems?
The are a few common approaches that are usually taken by APS systems to solve the problem of production scheduling they are:
Note: In addition to using standard heuristics, you also have the possibility of defining your own based on unique algorithms with SAP Manufacturing for Planning and Scheduling (aka ePP/DS).
2. Mixed Integer Linear Programming: A mixed integer linear programming problem is a mathematical optimization or feasibility program in which some or all of the variables are restricted to be integers. The algorithms used to plan the entire supply chain network or multiple locations to generate production and procurement proposals would use these algorithms. SAP IBP Response & Supply and SAP Manufacturing for Planning and Scheduling PPO use this algorithm.
Bonus:
Note: The IBP Optimizer and SAP S/4HANA Manufacturing for Planning and Scheduling (ePP/DS) PPO complement each other. On the one hand, IBP Optimizer plans the entire supply chain network whereas ePP/DS PPO focuses on Manufacturing plants.
3. The Genetic Algorithm: The genetic algorithm is a method for solving both constrained and unconstrained optimization problems that is based on natural selection, the process that drives biological evolution. The genetic algorithm repeatedly modifies a population of individual solutions. At each step, the genetic algorithm selects individuals from the current population to be parents and uses them to produce the children for the next generation. Over successive generations, the population "evolves" toward an optimal solution. You can apply the genetic algorithm to solve a variety of optimization problems that are not well suited for standard optimization algorithms, including problems in which the objective function is discontinuous, nondifferentiable, stochastic, or highly nonlinear. The genetic algorithm can address problems of mixed integer programming, where some components are restricted to be integer-valued. The SAP Manufacturing for Planning and Scheduling detailed scheduling (DS) optimizer uses the genetic algorithm to create optimized production schedules.
Here’s a great Youtube video that takes you through the genetic algorithm.
What does the future look like for SAP S/4HANA Manufacturing for Planning and Scheduling (ePP/DS)?
The SAP S/4HANA Manufacturing for Planning and Scheduling solution with its roots in SAP APO is a mature application and now after being embedded to S/4HANA (additional add-on subscription) has a well defined roadmap with more features and functionalities across various dimensions being delivered to customers with each release. These areas of improvements include user experience, industry specific planning algorithms, cross app integration as well as architectural updates. To view the roadmap, click the link.
Supply chains today need planning solutions and APS systems form a critical piece of any end to end planning solution. With the increased adoption of Artificial and Machine learning , we will see new algorithms infused into APS systems to solve even harder planning problems. At the same time, user experience for these traditionally difficult to use applications will also see great improvements.
In conclusion, you now know more about the evolution of advanced planning systems like SAP S/4HANA Manufacturing for Planning and Scheduling (ePP/DS) and Integrated Business Planning. We have also delved into different types of planning approaches and algorithms these systems use. Lastly, we learnt how to view and know more future updates in the SAP Road Map Explorer.?
Senior IT Business Analyst @Unilever | MSc in Info. System | Certified Scrum Product Owner?
1 年Thanks for an insightful article ??
Senior SAP Industry Solutions Advisor - Director Presales at SAP Middle East & North Africa
2 年Great ?? Insights Thanks for sharing Jawad
Principal Consultant SAP S/4HANA Manufacturing,ePP/DS,PEO, IBP/Advance VC/Advance ATP/EAM at SAP India Pvt. Ltd
2 年Good one Jawad Khan .Keep writing.
SAP Presales, Digital Supply Chain
2 年It’s great article. Thank you Jawad Khan ??