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A blank dimension is not only a premise of blank design and manufacture, but also plays a significant role to decide the machining process and the energy consumption of the machining process. The design of an appropriate blank dimension is important to ensure efficient energy usage. However, consideration of a workpiece machining process and energy consumption during the machining process in the blank dimension design phase is often neglected. To design a blank dimension scientifically and effectively, this paper proposes an optimization approach for blank dimension design, by considering energy consumption, machine cost, and process time. The three objectives are affected by three variables, cutting depth, feed rate, and cutting speed. The non-dominated sorting genetic algorithm-II (NSGA-II) algorithm was used to solve multi-objective optimization problem, and blank dimensions could be calculated from the cutting depth of minimum energy consumption and workpiece dimension. The results indicated that the proposed approach is effective in realizing energy savings due to the appropriate blank dimension design. The optimization approach not only offers some insights for designing a new blank dimension, but also provides a theoretical basis for existing blank dimension selection. [ABSTRACT FROM AUTHOR]

The environmental impacts of the manufacturing stage of the product life cycle are resource consumption and waste emissions. The development of an appropriate assessment method for evaluating the environmental performance of a manufacturing process, or an entire process plan, is one of the keys to realize a successful sustainable manufacturing strategy. This paper describes a new method for the environmental evaluation of a manufacturing process plan, where actual values for various environmental measures for the different operations in the plan are used to form an impact matrix. If desired, scores for each process, each environmental measure, and for the entire plan may be obtained by applying weights obtained from the analytical hierarchy process. The method has been encoded in software (Manufacturing Environmental Performance Evaluation), which provides insights into how manufacturing decisions affect the environment. A case study is used to illustrate how the assessment method may be applied and to demonstrate its applicability. [ABSTRACT FROM AUTHOR]