Energy Efficient Manufacturing: Theory and Applications

By John W. Sutherland and David A. Dornfeld

Over the last several years, manufacturers have expressed increasing interest in reducing their energy consumption and have begun to search for opportunities to reduce their energy usage. In this book, the authors explore a variety of opportunities to reduce the energy footprint of manufacturing. These opportunities cover the entire spatial scale of the manufacturing enterprise: from unit process-oriented approaches to enterprise-level strategies. Each chapter examines some aspect of this spatial scale, and discusses and describes the opportunities that exist at that level. Case studies demonstrate how the opportunity may be acted on with practical guidance on how to respond to these opportunities.

• Language: English
• Publisher: Wiley
• Release date: Jul 24, 2018
• ISBN: 9781119521372

Book preview

Contents

Cover

Title page

Copyright page

Dedication

Chapter 1: Introduction to Energy Efficient Manufacturing

1.1 Energy Use Implications

1.2 Drivers and Solutions for Energy Efficiency

References

Chapter 2: Operation Planning & Monitoring

2.1 Unit Manufacturing Processes

2.2 Life Cycle Inventory (LCI) of Unit Manufacturing Process

2.3 Energy Consumption in Unit Manufacturing Process

2.4 Operation Plan Relevance to Energy Consumption

2.5 Energy Accounting in Unit Manufacturing Processes

2.6 Processing Energy in Unit Manufacturing Process

2.7 Energy Reduction Opportunities

References

Chapter 3: Materials Processing

3.1 Steel

3.2 Aluminum

3.3 Titanium

3.4 Polymers

References

Chapter 4: Energy Reduction in Manufacturing via Incremental Forming and Surface Microtexturing

4.1 Incremental Forming

4.2 Surface Microtexturing

4.3 Summary

4.4 Acknowledgement

References

Chapter 5: An Analysis of Energy Consumption and Energy Efficiency in Material Removal Processes

5.1 Overview

5.2 Plant and Workstation Levels

5.3 Operation Level

5.4 Process Optimization for Energy Consumption

5.5 Conclusions

Reference

Chapter 6: Nontraditional Removal Processes

6.1 Introduction

6.2 Energy Efficiency

Acknowledgments

References

Chapter 7: Surface Treatment and Tribological Considerations

7.1 Introduction

7.2 Surface Treatment Techniques

7.3 Coating Operations

7.4 Tribology

7.5 Evolving Technologies

7.6 Micro Manufacturing

7.7 Conclusions

References

Chapter 8: Joining Processes

8.1 Introduction

8.2 Sustainability in Joining

8.3 Taxonomy

8.4 Data Sources

8.5 Efficiency of Joining Equipment

8.6 Efficiency of Joining Processes

8.7 Process Selection

8.8 Efficiency of Joining Facilities

8.9 Case Studies

Reference

Chapter 9: Manufacturing Equipment

9.1 Introduction

9.2 Power Measurement

9.3 Characterizing the Power Demand

9.4 Energy Model

9.5 Life Cycle Energy Analysis of Production Equipment

9.6 Energy Reduction Strategies

9.7 Additional Life Cycle Impacts of Energy Reduction Strategies

9.8 Summary

References

Chapter 10: Energy Considerations in Assembly Operations

10.1 Introduction to Assembly Systems & Operations

10.2 Fundamentals of Assembly Operations

10.3 Characterizing Assembly System Energy Consumption

10.4 Direct Energy Considerations of Assembly Joining Processes

10.5 Assembly System Energy Metrics

10.6 Case Study: Heavy Duty Truck Assembly

10.7 Future of Energy Efficient Assembly Operations

References

Appendix 10.A

Chapter 11: Manufacturing Facility Energy Improvement

11.1 Introduction

11.2 Auxiliary Industrial Energy Consumptions

11.3 Industrial Practices on Energy Assessment and Energy Efficiency Improvement

11.4 Energy Management and Its Enhancement Approaches

11.5 Conclusions

References

Chapter 12: Energy Efficient Manufacturing Process Planning

12.1 Introduction

12.2 The Basics of Process Planning

12.3 Energy Efficient Process Planning

12.4 Case Study

12.5 Conclusions

Reference

Chapter 13: Scheduling for Energy Efficient Manufacturing

13.1 Introduction

13.2 A Brief Introduction to Scheduling

13.3 Objective Functions for Energy Efficiency

13.4 An Integer Linear Program for Scheduling an Energy-Efficient Flow Shop

13.5 Conclusion and Additional Reading

References

Chapter 14: Energy Efficiency in the Supply Chain

14.1 Supply Chain Management

14.2 Supply Chain Structure

14.3 Supply Chain Processes

14.4 Supply Chain Management Components

14.5 Conclusion

References

Endnotes

Chapter 15: Business Models and Organizational Strategies

15.1 Introduction

15.2 Reference Framework for Selection of Energy Efficiency Projects

15.3 Common Energy Efficiency Opportunities

15.4 Stakeholders

15.5 Conclusions

References

Chapter 16: Energy Efficient or Energy Effective Manufacturing?

16.1 Energy Efficiency: A Macro Perspective

16.2 The Basics of Energy Efficiency

16.3 Limitations of Energy Efficiency

16.4 Energy Effectiveness

16.5 Summary

16.6 Acknowledgments

References

Index

End User License Agreement

List of Illustrations

Chapter 1

Figure 1.1 Energy consumption in the USA by sector [5].

Figure 1.2 Average retail prices of electricity [5].

Figure 1.3 Structure of the book.

Chapter 2

Figure 2.1 Process chain of unit processes to manufacture bearing race.

Figure 2.2 Energy and material inputs and outputs for unit manufacturing process.

Figure 2.3 Taxonomy of manufacturing processes.

Figure 2.4 Overview of the CO2PE! UPLCI—framework [9].

Figure 2.5 Overview of the process inventory phase for the in-depth approach [9].

Figure 2.6 Energy supplies to manufacturing [16].

Figure 2.7 LCI system boundary of a machining process.

Figure 2.8 Processing energy model in forging of solid cylindrical workpiece.

Figure 2.9 Processing energy model for orthogonal cutting.

Figure 2.10 Power characteristics of machine tools [17].

Figure 2.11 Processing energy model for grinding.

Figure 2.12 Specific energy as a function of MRR [22].

Figure 2.13 Experimental setup of power measurement [27].

Figure 2.14 Process chain shortened by hard milling.

Figure 2.15 Increase of energy efficiency by using new technologies [28].

Figure 2.16 Hybrid milling-laser process.

Chapter 3

Figure 3.1 World crude steel production, 1970 to 2010 [2].

Figure 3.2 Total energy consumption of crude steel production for North America, Europe, and Japan, 1975 to 2005 [5].

Figure 3.3 Secondary aluminum production in the United States, 1940–2010 [18].

Figure 3.4 Global and United States production of aluminum, 1930–2012 [18].

Figure 3.5 Market share and price of aluminum for the United States, 1940-2010 [18].

Figure 3.6 End uses of aluminum, 1975-2003 [20].

Figure 3.7 Global market share of titanium alloys [27].

Figure 3.8 Titanium sponge consumption compared to mineral importation, 1928–2011 [28, 32, 33].

Figure 3.9 End uses of titanium sponge metal, 1975-2004 [34].

Figure 3.10 Titanium sponge price and consumption, along with several major global events, 1941-2011 [19, 35].

Figure 3.11 Global production of plastics, 1950–2012 [39].

Figure 3.12 Polymer products manufactured in the United States, 2012 [40].

Figure 3.13 Fabrication processes used in manufacturing polymer products [41].

Figure 3.14 Comparison of common polymer manufacturing processes [42].

Figure 3.15 Examples of shape complexity obtained with hybrid polymer-powder processes.

Figure 3.16 Market distribution of power semiconductor devices.

Figure 3.17 Overall environmental impact of electricity and total materials and energy [47].

Chapter 4

Figure 4.1 Schematic of (a) Single point incremental forming (b) Double sided incremental forming.

Figure 4.2 Classification of current flexible and sustainable forming processes.

Figure 4.3 Schematic of (a) Conventional stamping (b) MPD forming system

Figure 4.4 Schematic of (a) Flexible rolling setup (b) 3D view of flexible rolling process. [13].

Figure 4.5 Schematic of shot peen forming process (http://abrasivefinishingcompany.com/t-peen-forming.html)

Figure 4.6 Schematic of (a) Marform process [11] and the (b) Hydroforming process (http://www.thefabricator.com).

Figure 4.7 (a) Schematic of Explosive forming process.[15] (b) Schematic of Electromagnetic-die forming process.[15].

Figure 4.8 (a) Tools used in Incremental Forming (b) Experimental Forming Limit Curve for SPIF and conventional forming [19] (c) Conventional forming press, weight 8000 lbs (d) Incremental Forming machine, weight 2000 lbs.

Figure 4.9 Comparison of exergy consumption between Incremental Forming, hydroforming and conventional forming processes [9].

Figure 4.10 Schematic showing the technical challenges in incremental forming.

Figure 4.11 Schematic showing geometrical inaccuracy in SPIF.

Figure 4.12 Schematic showing toolpath in (a) DSIF out-to-in toolpath (b) ADSIF toolpath.

Figure 4.13 Schematic showing relative positioning of the top and the bottom tools.

Figure 4.14 (a) Comparison of parts formed with SPIF and DSIF out-to-in toolpaths (b) Comparison of geometric profiles of parts formed with SPIF and DSIF out-to-in toolpaths.

Figure 4.15 Schematic showing relative positioning of forming tool (top tool) and supporting tool (bottom tool) in ADSIF.

Figure 4.16 (a) Comparison of profiles of a 40° wall angle cone formed with SPIF, DSIF out-to-in and ADSIF toolpaths (b) Comparison of parts formed with SPIF, DSIF out-to-in and ADSIF toolpaths.

Figure 4.17 (a) 50° wall angle cone that fractures with SPIF and DSIF out-to-in toolpaths but not with the ADSIF toolpaths (b) Complex parts formed with ADSIF.

Figure 4.18 Custom built Incremental Forming Machine at Northwestern University.

Figure 4.19 Comparison of tool z forces between FEA and experiments for (a) 70° cone shape (b) funnel shape.

Figure 4.20 Contours of localization flag, z depth and plastic strain at (a) at onset of diffused necking (b) at onset of localized necking (c) just before fracture, for punch forming of the 70° cone.

Figure 4.21 Contours of localization flag, z depth and plastic strain at (a) at onset of diffused necking (b) at onset of localized necking (c) just before fracture, for SPIF of the 70° cone.

Figure 4.22 (a) Stretching the string at the free end (b) material localization at a single location on the string (c) Fracture at location of material localization (d) Stretching the string by ∆s at location ∆c from the free end (e) Continuous material localization along length of the string (f) elongation to a greater length without fracture.

Figure 4.23 Regions along the outer surface of SPIF components indicating material localization.

Figure 4.24 (a) Laser textured sample surface; the cylinder diameter is 18.75 mm. Laser texture features with a width of 100 microns, length of 400 microns, and depth of 25 microns (b) Three dimensional view of a portion of a bar-shaped dimple. Neglecting discontinuities, maximum depth is approximately 25 microns.

Figure 4.25 Schematic of the experimental setup. The strip is pulled at a constant velocity and pulling force is recorded.

Figure 4.26 Percentage reduction in coefficient of friction from a non-textured to a textured surface.

Figure 4.27 Laser micro-machining system, including a picosecond laser, a beam delivery system, and a 5 degree of freedom position stage.

Figure 4.28 Rastering trajectory for the creation of a rectangular surface texture feature. The green lines show the trajectory of the firing laser beam and the grey dashed lines show the trajectory followed while not firing.

Figure 4.29 Illustration of pulse overlap. Grey circles represent the placement of laser pulses and black dashed lines follow the path of the laser beam. (a) and (b) represent 50% and 75% overlap in X, respectively, and (c) represents 50% overlap in X and 50% overlap in Y.

Figure 4.30 (a) Schematic of LIP-MP (b) Plasma in LIP-MP using distilled water and a ps.

Figure 4.31 (a) CCD image of spot plasma (b) Optical arrangement for creating line plasma (c) CCD image of line plasma.

Figure 4.32 Channels machined on: (a) Polycarbonate (b) ABS (Power: 0.12 W, Frequency: 10 kHz, Dielectric: Distilled water, laser feed: 10 μm/s).

Figure 4.33 Channels machined on: a) Transparent alumina ceramic (b) Shiny silicon wafer (Power: 0.12 W, Frequency: 10 kHz, Dielectric: Distilled water, laser feed: 10 μm/s).

Figure 4.34 Channels machined on Polycarbonate with S-LIPMM and direct laser ablation (Power: 0.12 W, Frequency: 10 kHz, Dielectric: Distilled water, spot translated at 10 μm/s).

Figure 4.35 Channels machined on AA5052 with Line LIPMM (a) Optical view and depth plot of machined channels (b) cross sectional geometry of machined channels.

Figure 4.36 (a) Channel arrays on silicon machined using L-LIPMM (b) Alternating channel patterns on silicon using L-LIPMM.

Figure 4.37 (a) Schematic of rollers with microchannel features (b) CAD model and fabricated DμRM (c) Schematic of DμRM.

Figure 4.38 Schematic of Flexible Bearing House (FBH).

Figure 4.39 (a) Schematic of capacitive pressure sensor (b) Fabricated pressure sensor.

Figure 4.40 (a) Microroller used for texturing in [73] (b) Measurement of roll pressure as a function of set gap between rolls (c) Measurement of channel depth as a function of location along the roller axis.

Figure 4.41 (a) Multipass forming strategy for forming non-regular channels (b) Channels and textures formed using the DμRM setup and multipass forming strategy.

Figure 4.42 Deformed channel geometry (a) after one roll pass (b) after two roll passes (c) as a function of roll pass and set roll gap.

Chapter 5

Figure 5.1 Power requirement in the form of electricity used per unit mass of material processed for various manufacturing processes as a function of the rate of material processing [2].

Figure 5.2 Energy flow breakdown for a machining line [4].

Figure 5.3 Energy profile of a turning process [7].

Figure 5.4 Energy consumption per unit volume of material removed [10].

Figure 5.5 Energy contribution of the process at different cutting speed [10].

Figure 5.6 Energy efficiency of the process at different cutting speed [10].

Figure 5.7 Procedures of the energy saving approach [11].

Figure 5.8 Example of energy monitoring analysis across temporal scales [12].

Figure 5.9 Standby power of studied machine tools [13].

Figure 5.10 Component power of NH8000 milling machine [13].

Figure 5.11 EnergyBlocks methodology [20].

Figure 5.12 Time, energy consumption and energy cost results for the case study of cylinder head manufacturing [20].

Figure 5.13 Variation of cutting power with material removal rate for various materials [23].

Figure 5.14 Variation of energy efficiency with (a) cutting speed, (b) rake angle, (c) nose radius and (d) edge radius [26].

Figure 5.15 (a) Specific energy demand and its contributions, (b) as a function of lubrication/cooling conditions [27].

Figure 5.16 Population plot for optimization of dry machining process.

Figure 5.17 Population plot for optimization of MQL machining process.

Figure 5.18 Population plot for optimization of cryogenic machining process.

Figure 5.19 Total specific energy for 11SMnPB30 steel [25].

Figure 5.20 Composition of total specific energy for HSMnPb30 steel [25].

Figure 5.21 Comparison of measured and predicted forces under dry and cryogenic conditions (V = 100 m/min, f = 0.1 mm/rev) [30].

Figure 5.22 Specific energy of ANSI 1018 steel on the Mori Seiki NVD 1500 milling machine [16].

Figure 5.23 Measured and predicted electrical power consumption due to axis movement [31].

Figure 5.24 Cutting parameters in face milling [32].

Figure 5.25 (a) power measurement according to tool-wear progressed; (b) Power consumption measured [33].

Figure 5.26 Energy consumption and tool life in drilling cast iron with external flushing as a function of removal rate [34].

Figure 5.27 Comparison of energy consumption, tool cost and total cost in drilling for various flushing strategies as a function of material removal rate [34].

Figure 5.28 (a) Conventional acceleration method; (b) improved acceleration method [35].

Figure 5.29 Relationship between specific energy and maximum undeformed chip thickness [37].

Figure 5.30 Specific energy components for (a) conductive ceramic and (b) mild steel [38].

Figure 5.31 Environmental impact (CO2 Fossil) against material removal rate and surface roughness [39].

Figure 5.32 Specific grinding energy during grinding of EN24 steel using flood cooling and soybean-based lubricants [40].

Figure 5.33 Specific grinding energy during grinding of cast iron using flood cooling and paraffin-based lubricants [40].

Chapter 6

Figure 6.1 Schematic of Electro-Discharge Machining Process (right picture: Kunieda, M., Kruth, J. P., Rajurkar, K. P., Schumacher, M., Advancing EDM through Fundamental Insight into the Process. CIRP Annals - Manufacturing Technology, 2005. 54(2): p. 64–87).

Figure 6.2 Sequence of events in EDM process.

Figure 6.3 Illustration of the EDM process mechanism.

Figure 6.4 Schematic of electrochemical machining process.

Figure 6.5 Schematic of electrochemical discharge machining process.

Figure 6.6 Schematic of electrochemical grinding process.

Chapter 7

Figure 7.1 Increasing product complexity since the industrial revolution.

Figure 7.2 Specific energy requirements for various manufacturing processes including ancillary equipment. Source: After Gutowski et al., [2011], with additional processes included.

Figure 7.3 Development of the role of surface geometry Jiang et al., [4].

Figure 7.4 Surface classification hierarchy proposed Jiang et al., [4].

Figure 7.5 Outline of major surface treatment processes.

Figure 7.6 Application of laser texturing to a surface. (a) Crater with rims, as is used to reduce adhesion in computer hard drives; (b) Crater with rim removed, as is used to provide enhanced lubricant transport.

Figure 7.7 Schematic illustration of shot peening. (a) Illustration of a surface subjected to multiple impacts by spherical shot, with a detailed view emphasizing the thickness affected; (b) typical beneficial effects of shot peening on fatigue properties of metals. Source: (b) courtesy of J. Champaigne, Electronics Inc.

Figure 7.8 Typical induction hardening arrangements. Source: Courtesy of Kalpakjian and Schmid [2014].

Figure 7.9 Outline of the major coating processes.

Figure 7.10 Schematic illustrations of thermal-spray operations: (a) thermal wire spray, (b) thermal metal-powder spray, and (c) plasma spray. Source: From Kalpakjian and Schmid [2014].

Figure 7.11 Schematic illustration of the chemical-vapor-deposition process. Note that parts and tools to be coated are placed on trays inside the chamber. Source: From Kalpakjian and Schmid [2014].

Figure 7.12 Schematic illustration of the arc deposition process. Note that there are three arc evaporators and the parts to be coated are placed on a tray inside the chamber. Source: From Kalpakjian and Schmid [2014].

Figure 7.13 Schematic illustration of the sputtering process. Source: From Kalpakjian and Schmid [2014].

Figure 7.14 SEM images of phosphate coatings, from Bay [7]. (a) Needle structure; (b) grainy structure.

Figure 7.15 Schematic illustration of phosphate coating with soap coatings.

Chapter 8

Figure 8.1 (a) Distribution of energy consumption in U. S. manufacturing industry by energy carrier, (b) Distribution of energy consumption in U.S. semi-final and final metal production by energy carrier [5].

Figure 8.2 Qualitative energy flow for a joining process (adapted from [9]).

Figure 8.3 Classification of joining processes used in this chapter.

Figure 8.4 Photographs of devices for measuring electricity: (a) Fluke I5S 5A AC current probes, and (b) Fluke 1735 Three-Phase power logger (photographed at Technische Universität Chemnitz).

Figure 8.5 Representative schematic of power levels associated with energy consumption for a joining process.

Figure 8.6 Edge preparation for corner joint configurations [22].

Figure 8.7 Welding edge preparations for wide root openings. (a), (b), and (c) Backing bars. (d) Spacer bar [21].

Figure 8.8 Flow diagram for fusion arc welding process.

Figure 8.9 Flow diagram for oxy-acetylene gas welding process.

Figure 8.10 Flow diagram for torch brazing.

Figure 8.11 Flow diagram for mechanical fastening by nut-bolts.

Figure 8.12 Flow diagram for the adhesive bonding process.

Figure 8.13 Peripheral structure of a welding shop (adapted from [25]).

Figure 8.14 General model for energy efficiency measures in factories [31].

Figure 8.15 SAW - equipment diagram [38].

Figure 8.16 Schematic of Friction Stir Welding (UW-Madison).

Figure 8.17 Photograph of FSW tool superimposed on image of weld cross-section (images by UW-Madison).

Figure 8.18 Power characteristics for a representative friction stir weld.

Figure 8.19 Schematic of energy consumed in FSW

Chapter 9

Figure 9.1 A schematic of a three-phase, three-load, three-wire measurement.

Figure 9.2 Schematic representation of the components of AC power. Real power, P, is placed on the real axis since it transfers energy, while reactive power, Q, is placed on the imaginary axis since it does not transfer energy.

Figure 9.3 Power breakdown of a machine tool versus processing load (after Dahmus and Gutowski [4] and Diaz et al. [5]).

Figure 9.4 Power breakdown of a Mori Seiki NV4000 and NVD1500 with a spindle rotation of 3,500 rpm and feed rate of 300 mm/min (after Taniguchi et al. [6]).

Figure 9.5 Spindle power versus spindle speed of an array of small to large machine tools [7].

Figure 9.6 Specific energy model of a machine tool.

Figure 9.7 Energy consumed for part manufacture during the use phase of milling machine tools in a commercial facility (after Diaz et al. [14]).

Figure 9.8 Measured (a) final surface roughness and (b) full width at half maximum for varied feed rate, f, cutting speed, vc, and depth of cut, d, during either the rough or finish cuts as indicated; the baseline case is marked with an x [33].

Figure 9.9 Two energy reduction considerations for the product life cycle: (a) leverage increased manufacturing resources to improve part quality, and (b) reduce energy consumption of production equipment.

Chapter 10

Figure 10.1 Assembly in the context of the manufacturing enterprise [By permission of Oxford University Press, USA, MECHANICAL ASSEMBLIES: THEIR DESIGN, MANUFACTURE, AND ROLE IN PRODUCT DEVELOPMENT [5] Table 1.1 (adapted)].

Figure 10.2 Assembly system energy characterization tree.

Figure 10.3 Power density during welding processes (not to scale).

Figure 10.4 Total consumption by energy type.

Figure 10.5 Direct non-value added process by equipment.

Figure 10.6 Direct non-value added process by source.

Figure 10.7 Direct value added process by source.

Figure 10.8 Top direct energy intensive processes.

Chapter 11

Figure 11.1 U.S. energy consumption by economic sectors.

Figure 11.2 U.S. electricity mix. IEA, Annual Energy Review Report, 2006.

Figure 11.3 Manufacturing Energy Consumption by End-Use in California.

Figure 11.4 Percentage of total energy consumption in commercial building by end use [1].

Figure 11.5 Basic schematic of heating and cooling equipment and air handlers in an HVAC system [8].

Figure 11.6 Cost of energy delivery modes [10].

Figure 11.7 Levelized cost of energy efficiency compared to electric supply side options. Energy efficiency average program portfolio data from Molina 2013 (Courtesy of ACEEE) - forthcoming; All other data from Lazard 2012. High-end range of advanced pulverized coal includes 90% carbon capture and compression

Figure 11.8 Regression analysis of energy use and production data.

Figure 11.9 Energy Use in the Industrial Sector. Based on data from the U.S. Energy Information Agency, January 2012.

Figure 11.10 Source: U.S. EIA, Manufacturing Energy Consumption Survey, 2006.

Figure 11.11 Planning Cycle for Continuous Improvement.

Figure 11.12 Schematic of typical energy monitoring system (Drawn by author).

Chapter 12

Figure 12.1 Main Steps Involved in Product Design and Manufacturing (In practice, iterations among steps are often necessary).

Figure 12.2 A shaft example.

Figure 12.3 A semi-generative process planning method for reduced energy consumption.

Figure 12.4 CAD drawing of a shaft support.

Chapter 13

Figure 13.1 Machine environments.

Figure 13.2 Gantt chart for a feasible schedule in Example 2.1.

Figure 13.3 Gantt chart for an infeasible schedule in Example 2.1.

Figure 13.4 Gantt chart for a feasible schedule in Example 2.2.

Figure 13.5 Gantt chart for infeasible schedule in Example 2.2.

Figure 13.6 Gantt chart for a feasible schedule in Example 2.3.

Figure 13.7 Gantt chart for a feasible schedule in Example 3.1.

Figure 13.8 Possible start times for job j on machine i processed at speed s.

Figure 13.9 Possible start times for job j on machine i processed at speed s if it is being processed in period u.

Figure 13.10 Gantt chart for an optimal schedule for the EEFS problem in Example 4.2. The indices in parentheses indicate the speed at which the job is processed.

Chapter 14

Figure 14.1 Characteristics of supply chain structure.

Figure 14.2 Life-cycle energy of incandescent lamps, CFLs, and LED Lamps [42].

Chapter 15

Figure 15.1 Percentage of US energy consumption by sector.

Figure 15.2 Energy efficiency spending in the United States (billions).

Figure 15.3 Barriers to corporate energy efficient initiatives (% of respondents).

Figure 15.4 Reference model for project selection and adoption.

Figure 15.5 A general portfolio of energy efficiency projects.

Chapter 16

Figure 16.1 Global Improvements in Manufacturing Energy Efficiency (1990–2012) [2, 3].

Figure 16.2 ISO 50001 (Energy Management Systems) Annual Corporate Certifications[6].

Figure 16.3 Energy flows to perform a turning operation.

Figure 16.4 System diagram showing how energy supports lathe and other functions.

Figure 16.5 An example of where energy is lost prior to becoming useful work [Adapted from 10].

Figure 16.6 U.S. manufacturing sector primary energy use [11].

Figure 16.7 Schematic illustrating energy consuming elements in a turning process.

Figure 16.8 Energy consumption in manufacturing: From a scope perspective.

Figure 16.9 Constrained decision space and the challenge of considering multiple objectives.

Figure 16.10 Increased consumption overwhelms improvements in efficiency per part.

Figure 16.11 The energy efficiency challenge – Selecting the best pathway to get to the outcome.

Figure 16.12 The energy effectiveness challenge – Which outcome should be pursued?

Figure 16.13 Global carbon emissions trends – Total and per capita [17].

List of Tables

Chapter 2

Table 2.1a Operation conditions of machining relevant to energy consumption.

Table 2.1b Operation conditions of energy-beam based processes relevant to energy consumption.

Table 2.1c Operation conditions of forming processes relevant to energy consumption.

Chapter 3

Table 3.1 Emerging titanium processing technologies (Kraft 2004).

Table 3.2 Comparison of ceramic net-shaping processes.

Chapter 5

Table 5.1 Energy analysis of four milling machines [8].

Table 5.2 Machining parameters used in the experiments [28].

Table 5.3 Coolant application parameters used in the experiments [28].

Table 5.4 Optimal process parameters selected for all three coolant applications.

Table 5.5 Energy consumption and tool life from different cooling strategies [34].

Chapter 6

Table 6.1 Specific energy comparison.

Chapter 7

Table 7.1 Summary of heat treating processes involving chemical diffusion into surfaces.

Chapter 8

Table 8.1 Selected sustainability indicators for joining processes.

Table 8.2 Reference values for thermal efficiencies of joining processes [11].

Table 8.3 Devices for measuring the energy consumption of welding.

Table 8.4 Specific melting energy for some commonly welded metals [23].

Table 8.5 Filler metals and brazing temperatures for brazing various metals and alloys.

Table 8.6 Comparison of commonly used joining methods [24].

Table 8.7 Minimum fillet leg distance based on the larger workpiece thickness being joined [24, 40].

Table 8.8 Density of electrode metals used in submerged arc welding.

Table 8.9 Specific Weld Energy based on TWA [45].

Table 8.10 Friction stir welding parameters and tool dimensions.

Chapter 10

Table 10.1 Curing process advantages and disadvantages [20 – Copyright © 2012 (2008, 2004, 1997) John Wiley & Sons Inc.].

Table 10.2 Energy influencing advantages and disadvantages of primary joining methods.

Table 10.3 Case study energy sources with associated energy data.

Table 10.4 Case study assembly process categorization.

Table 10.5 Processing equipment of the assembly station.

Table 10.6 Annual energy consumption - Battery.

Table 10.7 Annual energy consumption - Pneumatic.

Table 10.8 Direct and indirect process equipment annual energy consumption.

Table 10.9 Energy intensity by source.

Appendix 10.A

Table 10.A.1 Extended Process Categorization

Chapter 11

Table 11.1 Technological characteristics of industrial lighting technologies.

Table 11.2 Summary of various heat loads in a manufacturing plant.

Table 11.3 Leakage rates (cfm) for different supply pressures and approximately equivalent orifice sizes [8].

Chapter 12

Table 12.1 Process steps of manufacturing a shaft.

Table 12.2 The main characteristics of different production types.

Table 12.3 Reference numbers for the classification of production type.

Table 12.4 Routing sheet.

Table 12.5 Operations list.

Table 12.6 Operations precedence code.

Table 12.7 Operations precedence code.

Table 12.8 The energy consumption and carbon emissions of the final process plan.

Chapter 13

Table 13.1 Processing times and release dates for Example 2.1.

Table 13.2 Processing times for Example 2.2.

Table 13.3 Processing times and due dates for Example 2.3.

Table 13.4 Processing times and power demand for Example 3.1.

Table 13.5 Processing times, power demand, and release dates for Example 4.2.

Chapter 14

Table 14.1 Supply chain processes.

Chapter 16

Table 16.1 Industrial End-Use Energy Efficiency Barriers (adapted from [7]).

Table 16.2 The Importance of Sustainability to My Organization’s Success Over the Next Few Years (adapted from [8]).

Table 16.3 Energy consuming elements of a machine tool (adapted from [9]).

Table 16.4 CTG Energy and Emissions for Automobile and Cell Phone [18].

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Energy Efficient Manufacturing

Theory and Applications

Edited by

John W. Sutherland

David A. Dornfeld

Barbara S. Linke

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Library of Congress Cataloging-in-Publication Data

Names: Sutherland, John W. (John William), 1958- editor. | Dornfeld, D. A.,

   editor. | Linke, Barbara S., editor.

Title: Energy efficient manufacturing : theory and applications / edited by

   John W. Sutherland, David A. Dornfeld and Barbara S. Linke.

Description: Hoboken, NJ : John Wiley & Sons; Beverly, MA : Scrivener

   Publishing, 2018. | Includes index. |

Identifiers: LCCN 2018010577 (print) | LCCN 2018015275 (ebook) | ISBN

   9781119519812 (pdf) | ISBN 9781119521372 (epub) | ISBN 9781118423844

   (cloth)

Subjects: LCSH: Manufacturing processes–Energy conservation. | Process

   control.

Classification: LCC TS183 (ebook) | LCC TS183 .E48 2018 (print) | DDC

   658.2/6–dc23

LC record available at https://lccn.loc.gov/2018010577

Dedication

In March 2016, our good friend and mentor Professor David A. Dornfeld passed away. Dave was a constant source of inspiration and was always ready with a kind word and helpful suggestions. He was a passionate teacher and innovative researcher who made pioneering contributions to the fields of precision and sustainable manufacturing. Dave’s good natured personality, irrepressible humor, and intelligence elevated every meeting and conference he attended. He was active in many societies and received numerous honors. Dave was very inclusive and promoted talent where he saw it. His legacy is the many students, post-docs, and colleagues who benefitted from his excellent support, guidance, and advice.

We will miss you Dave!

John W. Sutherland

West Lafayette, IN

Barbara S. Linke

Davis, CA

June 2018

Chapter 1

Introduction to Energy Efficient Manufacturing

Barbara S. Linke1* and John W. Sutherland2*

1Department of Mechanical and Aerospace Engineering University of California, Davis, USA

2Environmental and Ecological Engineering, Purdue University, West Lafayette, Indiana, USA

*Corresponding authors: [e-mail]; [e-mail]

Abstract

Over the last decade, manufacturers around the world have expressed increasing interest in reducing their energy consumption. It appears that there are at least two principal motivations for this interest: i) the emergence of policies and legislation related to carbon emissions due to energy generation, and ii) the rising cost of energy relative to other production costs. Thus, manufacturers have begun to search for opportunities to reduce their energy usage.

A recent study by Johnson Controls shows that the demand for facility projects that promote and introduce renewable energy have dramatically increased over the last ten years [1]. Cost reduction remains the primary driver, but energy security, customer and employee attraction, greenhouse gas reduction, enhanced reputation, government policy, and investor expectations are increasingly important for investment in renewable energy [1].

In this book, the authors explore a variety of opportunities to reduce the energy footprint of manufacturing; these opportunities cover the entire spatial scale of the manufacturing enterprise: from unit process-oriented approaches to enterprise-level strategies. Each chapter examines some aspect of this spatial scale, and discusses and describes the opportunities that exist at each point on the scale. Each chapter uses one or more case studies to demonstrate how the opportunity may be acted on. Our goal is to inform students, practicing engineers, and business leaders of energy reduction approaches that exist across the manufacturing enterprise and provide some guidance on how to respond to these opportunities.

Keywords: Introduction, energy consumption, energy efficiency, overview

1.1 Energy Use Implications

Energy is defined as the ability to do work. It can be neither created nor destroyed but can be changed from one form to another (First Law of Thermodynamics). The different forms of energy include kinetic, potential, heat, electric, light, chemical and nuclear. The different forms have different relevance in our daily life. The different forms of energy are such so that some conversions from one form to another are easier than others (e.g., chemical energy in oil is readily converted into heat and light through combustion, but it is difficult to convert electricity into nuclear energy, for example with particle accelerators) [2].

Worldwide we use about 500 EJ of energy per year [3]. Although energy cannot be destroyed, the useful energy decreases in most systems. In addition, theory-based energy requirements often significantly underestimate actual energy requirements. For example, reduction of iron oxide to iron theoretically requires 7.35 MJ/kg of energy, but generally consumes 20 MJ/kg in industrial practice [2]. Theoretical energy and the actual energy consumed by industry differ because of energy losses at various steps in every process. A recent DOE bandwidth study estimated the potential energy savings opportunities for the U.S. Iron and Steel Manufacturing Sector as 240 TBtu (or 256 PJ) [4]. These savings could occur if the best technologies and practices available today were used to upgrade production. The savings would be 39% of the thermodynamic minimum or the minimum amount of energy theoretically required for these processes assuming ideal conditions.

Energy use may be attributed to four principal end-uses: transportation, residential, commercial, and industrial consumption, with each end-use roughly representing one-quarter of the total U.S. consumption (please refer to Figure 1.1). Manufacturing accounts for about 90% of industrial energy consumption and 84% of energy-related CO2 emissions (construction, mining, and agricultural activities account for the remaining industry sector contributions).

Graphic

Figure 1.1 Energy consumption in the USA by sector [5].

Manufacturing sector activities generate carbon dioxide and other greenhouse gas (GHG) emissions directly through onsite energy consumption (onsite generation and process energy), as well as indirectly through energy consumption to support non-process operations (e.g., facility HVAC – Heating, Ventilation and Air Conditioning, lighting, and onsite transportation). On a global scale, industry accounts for 21% of the total emissions generated [6]. Climate scientists report that these emissions upset the natural carbon balance of earth’s systems [7]. As actions are demanded to reduce GHG, it should be noted that such emissions are largely proportional to energy consumption. Further, environmental impacts from electricity generation and transmission include the physical footprint of the power plant, carbon dioxide and monoxide, sulfur dioxide, nitrogen oxides, particulate matter, heavy metals, and liquid and solid wastes.

1.2 Drivers and Solutions for Energy Efficiency

Around the globe industry is facing pressure from governments in the form of regulations, penalties, or tax benefits to reduce GHG emissions. For example, the Global Warming Solutions Act of 2006 (AB32) is a California State Law to reduce GHG emissions throughout California by 2020 [8]. It applies to 6 GHG contributors: CO2, CH4, NOx, hydrofluorocarbons, perfluorocarbons, and SF6. The European Union Emissions Trading System (EU ETS) has set a cap on GHG emissions and allows trading of ‘allowances’ [9].

Energy prices are increasing (Figure 1.2) and using energy more efficiently is therefore in the best interest of companies and part of their continuous improvement efforts. Furthermore, depending upon an acquired resource always involves a financial risk. This includes electricity, gasoline, and natural gas. Electricity at peak hours of demand costs more than at off-peak times. In addition, companies pay a cost penalty for low power factors. The power factor describes the ratio between real power (consumed power that does useful work) and apparent power (includes added load from capacitors or inductors) in an AC electrical circuit. Since power plants have to generate enough electricity to satisfy the apparent power, industrial consumers must pay additional costs for low power factors.

Graphic

Figure 1.2 Average retail prices of electricity [5].

In addition to pressure from governmental regulations and energy prices, companies are always striving to increase their competitiveness and enhance their market share. Growing pressure from society, consumers, and customers to become greener and more environmentally-friendly also drives manufacturers to reduce energy usage.

The U.S. Department of Energy has initiated many initiatives to help American companies become leaders in the use and production of clean energy technologies like electric vehicles, LED bulbs, and solar panels and to increase their energy productivity (output per unit of energy input) by implementing energy efficiency measures. Manufacturing data is key to achieving higher energy efficiency. For example, smart manufacturing, which is receiving increasing attention, seeks to use data from ubiquitous sensors across the manufacturing enterprise to increase throughput, improve quality, and reduce environmental impacts.

Dornfeld and Wright suggested that rather than implementing one solution, that technology wedges should be adopted to offer a better framework for addressing the manufacturing energy challenge [10]. Technology wedges are the manufacturing equivalent of the stabilization wedges concept introduced by Pacala and Socolow [11]. Stabilization wedges can reduce GHG through efficient cars, efficient buildings, wind power instead of coal power, reinventing land use rather than deforesting, etc. – in short, employing alternative technologies to reduce fossil fuel consumption through demand-side (consumptive) technology and supply-side (generative) technology changes. Both concepts highlight the gap between the current trends in consumption rate with respect to fossil fuel consumption/emission and movement towards a sustainable rate with respect to the atmosphere’s capability to accommodate emissions [10]. Instead of seeking a single solution to fill this gap, smaller wedges, such as simpler, single technologies should be introduced to reduce consumption rates. Manufacturing engineers have the power to embed technology wedges in their processes, manufacturing equipment, factories, business operations, and supply chains. This book explores some technology wedges for energy reduction.

Overview of the Book Contents

This book presents a variety of opportunities to reduce the energy footprint of manufacturing, mainly for discrete product manufacturing. These opportunities cover the entire spatial scale of the manufacturing enterprise: from unit process-oriented approaches to enterprise-level strategies. Each chapter examines some aspect of this spatial scale, and discusses and describes the opportunities that exist at that level (Figure 1.3). The book is therefore divided into three sections:

Graphic

Figure 1.3 Structure of the book.

Section I. Manufacturing Processes

In order to identify, analyze, and improve energy efficiencies, an enterprise must have a clear understanding of the performance of its manufacturing processes and the effect of process parameters on the energy consumption of unit processes. The primary focus of this section is therefore on the energy consumed by unit processes, explained by the physical principles associated with each process. Each chapter in this section will describe the physics of the manufacturing process and how energy is utilized, discuss energy reduction opportunities, and present a case study.

Chapter 2 lays the ground work for explaining the terminology for this book, in particular power, energy, and work. The energy for a unit manufacturing process is classified into four parts: processing, machine tool, process peripherals, and background. Processing energy can be modeled using a first principles approach, which will be demonstrated with examples from forging, orthogonal cutting, and grinding.

Chapter 3 focuses on raw material processing, which remains one of the most energy intensive phases in the product life cycle. This chapter provides an overview of the steel, aluminum, titanium, and polymer industries and describes the related materials processing technologies.

Chapter 4 discusses deformation processes, in particular the general concept, geometric accuracy, surface finish, formability prediction, and energy consumption of incremental forming in comparison with conventional forming. Surface texturing is introduced as a strategy to save energy by reducing friction at moving interfaces.

Chapter 5 reviews machining processes and the energy for machine tools and machining lines, discusses how energy depends on the material removal rate, and gives strategies for process optimization with regard to energy consumption. A detailed case study illustrates the optimization for minimal energy consumption in a turning process. Further studies address power consumption in turning, milling, drilling and grinding processes.