This chapter contains sections titled: Introduction Power Measurement Characterizing the Power Demand Energy Model Life Cycle Energy Analysis of Production Equipment Energy Reduction Strategies Additional Life Cycle Impacts of Energy Reduction Strategies Summary

Production engineering faces the challenge to satisfy the increasing industrial demand for higher productivity and high requirements on workpiece quality at the same time. Furthermore, the rising environmental awareness adds additional constraints. Especially grinding processes have high relevance for industrial applications because they generate high quality surfaces and they are most effective for hard-tomachine materials. New technologies like speed-stroke grinding and high cutting speeds enable higher productivity. However, to be competitive to conventional grinding operations energy aspects have to be regarded thoroughly. This work shows how the combination of speed-stroke grinding and high speed machining can boost process performance, workpiece quality and process sustainability.

In many instances, humans accomplish recognition by a Gestalt comparison of the feature with a catalog, either in hand or in memory. Some recognition tasks require an extensive catalog and organization, as represented by the typical field guides for identifying birds, plants, and so on. The horizontal axis of each plot is the magnitude of the differences in the parameters for each airplane shape. One thing that cross-correlation is quite good at is finding a feature in a cluttered or camouflaged scene. In some situations, such as searching reconnaissance images for objects of military interest, the cross-correlation is performed with target images oriented at angles in steps of about 15 to 20 degrees. When shape is used for classification, choosing the appropriate shape parameters may be done by humans based on prior knowledge and experience, or mathematically by techniques such as principal components analysis …

Production engineering is under constant pressure to satisfy demands for improved productivity while simultaneously achieving high workpiece quality. In addition, environmental awareness is a growing concern to address. New technologies represent new opportunities for increased productivity. This paper shows how the combination of speed stroke grinding and high speed machining can boost both process performance and workpiece quality. Theoretical consideration is validated by experiments and analyzed regarding energetic and environmental aspects. Only a thorough choice of process parameters leads to high process sustainability. Furthermore, lower tensile stresses can positively leverage increased manufacturing effort to optimize the overall product life cycle.

The environmental impact of most consumer products is dominated by their use phase. However, these impacts tend to be driven by the manufacture of the product's components since components fabricated with higher precision typically allow the product to operate at higher efficiencies. This paper investigates the relationship between precision and life cycle environmental impacts by extending the traditional LCA methodology to evaluate the impact of manufacturing process precision on the functional performance of a product during its use phase. The implications of this relationship to manufacturing decision-making are also discussed as sustainability concerns may support the use of higher precision processes.

Precise tool length measurement and work coordinate setup have been challenging tasks in ultra-precision machining. An acoustic emission (AE) sensor can be used to do both tasks at the same time based on AE generated on contact. First, a parametric study was conducted to identify the relationship between damage on the workpiece and key parameters. Second, two approaches, continuous and incremental, were proposed to minimize the potential damage to the workpiece surface. The incremental method produced much smaller damage while the continuous method minimized the setup time. Proper selection of either method depending on the application would improve the precision of tool length and work coordinate setup.

In this study, we performed a specific precision grinding process in an attempt to improve the mirror-quality finish and tribological characteristics of titanium nitride based coating films (TiN, TiCN, and TiAIN). The ground surfaces were highly smooth with no evidence of cracking, chipping, or peeling, demonstrating that the hard coating films were finished uniformly. For the TiAIN coating, a significant high level mirror-quality finish was achieved with an average roughness Ra of 4nm. In addition, for all films, the employed grinding process led to superior tribological characteristics. In the case of the TiN film, the precision grinding process produced a carbon- and copper-rich surface layer, as well as higher compressive residual stress.

—Given the exponential growth of the semiconductor industry, it is critical to assess the life-cycle energy demand of its products for appropriate eco-design in nanoelectronics. For computational logic applications, life-cycle energy demand is highly application dependent. In this paper, we study the life cycle of CMOS logic chips for five computational logic applications: from high-performance 32 nm CPUs for servers and laptops to low-power 45 nm processors for set-top boxes and smart phones to ultra-low-power 130 nm MCUs for RFID tags and sensors. For each chip, we model the energy demand for the CMOS processing step of integrated circuit manufacturing as well as for their use phase including both active and stand-by modes. While use-phase energy in active mode is almost two orders of magnitude higher than CMOS processing energy for high-performance CPUs, the energy demand for ultra-low-power MCUs is completely dominated by CMOS processing energy.

The presence of solid particle contaminant chips in high performance and complex automotive components like cylinder heads of internal combustion engines is a source of major concern for the automotive industry. Current industrial cleaning technologies, simply relying on the fluid transport energy of high pressure or intermittent high impulse jets discharged at the water jacket inlets of the cylinder head, fail to capture the dynamics of interaction between the chip morphology and the complex workpiece landscape. This work provides a preliminary insight into an experimental investigation of the mechanics of chip transport at play, and how it can be used to build an effective chip optimization model that significantly aids in improving the cleanability of contaminant chips. The objective is to relate the mechanics of chip transport with the chip form parameters as much as possible, which makes the objective and constraints in the optimization model quantifiable. The end objective is of course to transmit this information upstream of the manufacturing pipeline in the form of a Design for Cleanability (DFC) feedback, which highlights the industrial cleaning problem as a design centric issue.

Reducing the energy consumption of machine tools can significantly improve the environmental performance of manufacturing systems. To achieve this, monitoring of energy consumption patterns in the systems is required. It is vital in these studies to correlate energy usage with the operations being performed in the manufacturing system. However, this can be challenging due to complexity of manufacturing systems and the vast number of data sources. Event stream processing techniques are applied to automate the monitoring and analysis of energy consumption in manufacturing systems. Methods to reduce usage based on the specific patterns discerned are discussed.

CIRP has had a long history of research and publication on the development and implementation of sensor monitoring of machining operations including tool condition monitoring, unmanned machining, process control and, more recently, advanced topics in machining monitoring, innovative signal processing, sensor fusion and related applications. This keynote follows a recent update of the literature on tool condition monitoring and documents the work of the cutting scientific technical committee in CIRP. The paper reviews the past contributions of CIRP in these areas and provides an up-to-date comprehensive survey of sensor technologies, signal processing, and decision making strategies for process monitoring. Application examples to industrial processes including reconfigurable sensor systems are reported. Future challenges and trends in sensor based machining operation monitoring are presented.

Increasing demands on function and performance call for burr-free workpiece edges after machining. Since deburring is a costly and non-value-added operation, the understanding and control of burr formation is a research topic with high relevance to industrial applications. Following a review of burr classifications along with the corresponding measurement technologies, burr formation mechanisms in machining are described. Deburring and burr control are two possible ways to deal with burrs. For both, an insight into current research results are presented. Finally, a number of case studies on burr formation, control and deburring along with their economic implications are presented.

The surface quality and the dimensional accuracy are important criteria for micro-mold production, specially for micro-fluidic devices. Important cutting parameters that affect the quality of vertical side walls created by the peripheral cutting edge in micro-end-milling operations were identified. Surface roughness and form error were used to define the quality of side walls on stainless steel and aluminum workpieces. An acoustic emission sensor was used to detect initial contact between a tool and a workpiece for higher dimensional accuracy where the referencing is a critical element for precision micromachining feature creation.

The range of and particularly the minimum surface roughnesses achievable mainly with cemented carbide but also with single crystal diamond round nosed turning and facing inserts has been experimentally studied, machining aluminium and steel on engineering and precision lathes. Characteristic variations of machined surface profile with feed rate as well as insert edge sharpness and roughness measurements are reported. For aluminium faced by carbide inserts on precision lathes, insert edge radius (re) rather than feed marks determined Rz at low feeds, with Rz ≈0.02re. For steel work material, its properties rather than the insert edge radius became the Rz determining factor.

The range of surface roughnesses, and particularly the minimum roughnesses, achievable mainly with cemented carbide but also with single crystal diamond round nosed turning and facing inserts, has been experimentally studied, machining aluminium on engineering and precision lathes. Insert edge sharpness and roughness measurements and characteristic variations with feed rate of machined surface profile are presented. When machine tool limits are avoided, Rz values down to 0.02 times the insert edge radii have been obtained.

The range of surface roughnesses, and particularly the minimum roughnesses, achievable mainly with cemented carbide but also with single crystal diamond round nosed turning and facing inserts, has been experimentally studied, machining aluminium on engineering and precision lathes. Insert edge sharpness and roughness measurements and characteristic variations with feed rate of machined surface profile are presented. When machine tool limits are avoided, Rz values down to 0.02 times the insert edge radii have been obtained.

In this paper, three different sensors were used to measure multi-scale phenomena in chemical mechanical planarization. A piezoelectric force sensor, Hall effect sensor and acoustic emission sensor (AE) were installed in CMP equipment and the signals were measured simultaneously during the polishing process. The results showed that the sensors measuring frictional behaviour, such as the Hall effect sensor and force transducer, produced a clear end point signal in the case of the friction characteristics are distinguishable for each material. Also, if there is difference in hardness between materials, then a sharp end point signal is detected with the AE sensor even though the friction characteristic is similar between the two materials. Therefore, using multi-sensors having different bandwidths is complementary for not only process monitoring but also end point detection.

For practical application of micromechanical machining, four levels of process realization are required; fundamental understanding of process physics, development of microplanning (processing parameter optimization), macroplanning (tool path planning), and design optimization. This study surveyed the influence of localized variation in the microstructure on final process outcome and machinability of brittle optical material in a ductile regime. A clear correlation between burr height, critical depth of cut and crystallographic orientation was found on single crystal materials (copper and magnesium fluoride), giving insight into optimal orientations and process parameters for acceptable micromachining process outcome.