Increasing attention has recently been drawn to the energy consumption of the manufacturing process. Manufacturers are facing challenges from society of reducing emissions and operating more efficiently because of rising raw material prices and energy costs. Manufacturers are trying to balance among the total energy, economic and environmental targets simultaneously, a strategy that can be self-conflicting at times. This paper focuses on the objective optimizations of a plantlevel energy supply system, and describes how a multiobjective optimization strategy can be effectively formulated for making the best use of energy delivered to the manufacturing process. An example from an automotive assembly manufacturer is described.

Increasingly strict fuel efficiency standards have driven the aerospace and automotive industries to improve the fuel economy of their fleets. A key method for feasibly improving the fuel economy is by decreasing the weight, which requires the introduction of materials with high strength to weight ratios into airplane and vehicle designs. Many of these materials are not as formable or machinable as conventional low carbon steels, making production difficult when using traditional forming and machining strategies and capital. Electrical augmentation offers a potential solution to this dilemma through enhancing process capabilities and allowing for continued use of existing equipment. The use of electricity to aid in deformation of metallic materials is termed as electrically assisted manufacturing (EAM). The direct effect of electricity on the deformation of metallic materials is termed as electroplastic effect. This paper presents a summary of the current state-of-the-art in using electric current to augment existing manufacturing processes for processing of higher-strength materials. Advantages of this process include flow stress and forming force reduction, increased formability, decreased elastic recovery, fracture mode transformation from brittle to ductile, decreased overall process energy, and decreased cutting forces in machining. There is currently a lack of agreement as to the underlying mechanisms of the electroplastic effect. Therefore, this paper presents the four main existing theories and the experimental understanding of these theories, along with modeling approaches for understanding and predicting the electroplastic effect.

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Tool condition monitoring (TCM) is an important aspect of condition based maintenance (CBM) in all manufacturing processes. Recent work on TCM has generated significant successes for a variety of cutting operations. In particular, lower cost and on-board sensors in conjunction with enhanced signal processing capabilities and improved networking has permitted significant enhancements to TCM capabilities. This paper presents an overview of TCM for drilling, turning, milling, and grinding. The focus of this paper is on the hardware and algorithms that have demonstrated success in TCM for these processes. While a variety of initial successes are reported, significantly more research is possible to extend the capabilities of TCM for the reported cutting processes as well as for many other manufacturing processes. Furthermore, no single unifying approach has been identified for TCM. Such an approach will enable the rapid expansion of TCM into other processes and a tighter integration of TCM into CBM for a wide variety of manufacturing processes and production systems.