Modeling and Solution Algorithms for Process and Operations Planning with Applications in Manufacturing and Related Sectors

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Modeling and Solution Algorithms for Process and Operations Planning in Manufacturing Canadian manufacturing system must sustain its high-tech and economic edge by accelerating the adoption of new technologies and processes. Hybrid Manufacturing (HM) is an inevitable future choice of the flexible manufacturing system. It combines additive (AM) and subtractive manufacturing (SM) and offers great advantages including improvements in accuracy, speed, quality, as well as a positive environmental impact. The goal of this proposal is to improve the decision-making process for HM through the development and testing of design and planning functions. This will be accomplished by achieving the following four objectives. The first objective is to develop a design for HM (DfHM) guidelines, integrate the guidelines with a Computer Aided Manufacturing (CAM) or Digital Manufacturing (DM) system, and build parts and test them. The second is to develop a mathematical model and solution approach for HM macro-process planning for both manufacturing and remanufacturing problems. To explain this further, given a new product specification, the aim is to find an optimal grouping, orientation, and sequence of the AM and SM processes. The model and solution algorithms will be integrated with a CAM or DM system and tested with actual industrial-sized large manufacturing and remanufacturing problems. The third objective is to develop a mathematical model and solution approach for HM micro-process planning i.e., to find the optimal HM parameters and batch size to minimize machining costs, holding expenses, cost of quality, and environmental impact. The model and solution approach will be integrated with a CAM or DM system and tested by building actual physical parts. Lastly, the fourth objective is to develop a model and a solution procedure to design a platform under uncertain circumstances and to schedule the manufacturing and remanufacturing of a family of parts. The ultimate aim of these combined four objectives is to integrate mathematical models and solution procedures into a CAM or DM system. It is known that HM is creating success stories. With further research, HM can lead the way in industry especially for industrial cities like Windsor, Ontario. More investigation needs to be developed in this sector, building on the past contributions.