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

加拿大制造系统必须通过加速采用新技术和新工艺来保持其高科技和经济优势。混合制造是柔性制造系统未来的必然选择。它结合了增材制造（AM）和减法制造（SM），并提供了巨大的优势，包括精度、速度、质量的提高，以及对环境的积极影响。该提案的目标是通过设计和规划功能的开发和测试来改善HM的决策过程。这将通过实现以下四个目标来实现。第一个目标是开发HM （DfHM）指南的设计，将指南与计算机辅助制造（CAM）或数字制造（DM）系统集成，并构建零件并对其进行测试。二是针对制造和再制造问题，建立机械制造宏观工艺规划的数学模型和求解方法。为了进一步解释这一点，给定一个新的产品规格，目标是找到AM和SM过程的最佳分组、方向和顺序。模型和解决算法将与CAM或DM系统集成，并通过实际工业规模的大型制造和再制造问题进行测试。第三个目标是开发HM微工艺规划的数学模型和解决方法，即找到最佳HM参数和批量大小，以最小化加工成本，保持费用，质量成本和环境影响。模型和解决方法将与CAM或DM系统集成，并通过构建实际物理部件进行测试。最后，第四个目标是建立一个不确定环境下的平台设计模型和求解过程，并对一系列零件的制造和再制造进行调度。这四个目标的最终目的是将数学模型和解决程序集成到CAM或DM系统中。众所周知，HM正在创造成功的故事。通过进一步的研究，HM可以在工业方面领先，特别是在像温莎，安大略省这样的工业城市。在过去的贡献的基础上，需要在这个部门开展更多的调查。

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.