log c = log o + (log T - log T o ) where o is the cumulative MTBF at the start of the monitoring period T o . Therefore: (Eq 22) The slope gives an indication of the rate of MTBF growth and thus of the effectiveness of the reliability program in correcting failure modes. Duane (Ref 35) observed that typically ranges between 0.2 and 0.4 and correlates with the intensity of effort on improvement with higher numbers indicating greater intensity. O'Connor (Ref 6) provides a good discussion with an example. Spradlin (Ref 36) provides an excellent example of using the Duane method to improve reliability. Other examples are provided in Ref 37, 38, 39, 40, 41, 42, 43, 44, and 45. References cited in this section 6. P.D.T. O'Connor, Practical Reliability Engineering, 2nd ed., John Wiley & Sons, Inc., 1985 35. J.J. Duane, Learning Curve Approach to Reliability Modeling, IEEE Transactions, Aerospace, 2, 1964, p 563-566 36. B.C. Spradlin, Reliability Growth Measurements Applied to ESS, Annual Reliability and Maintainabilit y Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1986, p 97-100 37. E. Demko, True Reliability Growth Measurement, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1986, p 92-96 38. J.N. Bower, Reliability Growth During Flight Test, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1986, p 101-106 39. C.T. Gray, A Modelling Framework for Reliability Growth, Annual Rel iability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1986, p 107-114 40. L.H. Crow, On the Initial System Reliability, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1986, p 115-119 41. J.C. Wronka, Tracking of Reliability Growth in Early Development, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1988, p 238-242 42. L.H. Crow, Reliability Growth Estimation With Missing Data II, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1988, p 248-253 43. A.W. Benton and L.H. Crow, Integrated Reliability Growth Testing, Annual Reliability a nd Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1989, p 160-166 44. D.B. Frank, A Corollary to Duane's Postulate on Reliability Growth, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1989, p 167-170 45. G.J. Gibson and L.H. Crow, Reliability Fix Effectiveness Factor Estimation, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1989, p 171-177 Reliability in Design Charles O. Smith, Engineering Consultant Conclusions Determining the reliability of a complex system can be difficult. In principle, proceeding methodically by starting with the simplest units, combining them into subsystems, and then combining the subsystems into the complete system, and determining reliability at each step will lead to the final system reliability. A most important aspect is establishing the criterion of adequate performance of the system. Although difficult, reliability of a system can be established; it is done regularly. Reliability in Design Charles O. Smith, Engineering Consultant References 1. C.O. Smith, Introduction to Reliability in Design, McGraw-Hill Publishing Co., 1976 2. R.A. Dovich, Reliability Statistics, ASQC Quality Press, 1990 3. H.E. Martz and R.A. Walker, Bayesian Reliability Analysis, John Wiley & Sons, Inc., 1982, Reprint, Krieger, 1991 4. P.D.T. O'Connor, Practical Reliability Engineering, 3rd ed. rev., John Wiley & Sons, Inc., 1995 5. P.D.T. O'Connor, Practical Reliability Engineering, 3rd ed., John Wiley & Sons, Inc., 1991 6. P.D.T. O'Connor, Practical Reliability Engineering, 2nd ed., John Wiley & Sons, Inc., 1985 7. C.O. Smith, "Elements of Probabilistic Design," paper presented at Interna tional Conference on Engineering Design (ICED), 23- 25 Aug 1988 (Budapest, Hungary), available from Heurista (Zurich, Switzerland) 8. C.O. Smith, Design Relationships and Failure Theories in Probabilistic Form, Nucl. Eng. Des., Vol 27, 1974, p 286-292 9. C.O. Smith, "Design of Pressure Vessels to Probabilistic Criteria," Paper M4/3 presented at 1st Intl. Conf. on Structural Mechanics in Reactor Technology, 20- 24 Sept 1971 (Berlin, Germany), available from Bundesanstalt für Materialprüfung (BAM) (Berlin, Germany) 10. C.O. Smith, "Design of Rotating Components to Probabilistic Criteria," Paper M5/10 presented at 3rd Intl. Conf. on Structural Mechanics in Reactor Technology, 1- 5 Sept 1975 (London, England), available from Bundesanstalt für Materialprüfung (BAM) (Berlin, Germany) 11. C.O. Smith, "Shrink Fit Stresses in Probabilistic Form," ASME Winter Annual Meeting, 10- 15 Dec 1978 (San Francisco, CA), ASME Book No. H00135, American Society of Mechanical Engineers 12. C.O. Smith, Design of Ellipsoidal and Toroidal Pressure Vessels to Probabilistic Criteria, J. Mech. Des., Vol 102, Oct 1980, p 787-792 13. C.R. Mischke, "A Rationale for Mechanical Design to a Reliability Specification," presented at ASME Design Technology Transfer Conference, 5-9 Oct 1974 (New York, NY) 14. C.R. Mischke, "Implementing Mechanical Design to a Reliability Specification," presented at ASME Design Technology Transfer Conference, 5-9 Oct 1974 (New York, NY) 15. E.B. Haugen, Probabilistic Mechanical Design, John Wiley & Sons, Inc., 1980 16. G.E.P. Box, W.G. Hunter, and J.S. Hunter, Statistics for Experimenters, John Wiley & Sons, Inc., 1978 17. C. Lipson and N.J. Sheth, Statistical Design Analysis of Engineering Experiments, McGraw- Hill Publishing Co., 1973 18. J.D. Hromi, "Some As pects of Designing Industrial Test Programs," Paper 690022, Society of Automotive Engineers, Jan 1969 19. W.G. Cochran and G.M. Cox, Experimental Designs, John Wiley & Sons, Inc., 1950 20. D.R. Cox, Planning of Experiments, John Wiley & Sons, Inc., 1958 21. G.E.P. Box and J.S. Hunter, The 2 k-p Fractional Factorial Designs, Technometrics: Part I, Vol 3 (No. 3), Aug 1961, p 311-351; Part II, Vol 3 (No. 4), Nov 1961, p 449-458 22. G.E.P. Box, N.R. Draper, and J.S. Hunter, Empirical Model-Building and Response Surfaces, John Wiley & Sons, Inc., 1986 23. W.J. Hill and W.G. Hunter, A Review of Response Surface Methodology: A Literature Survey, Technometrics, Vol 8 (No. 4), Nov 1966, p 571-589 24. R. Mead and D.J. Pike, A Review of Response Surface Methodolog y From a Biometric Point of View, Biometrics, Vol 8, 1975, p 803 25. G.E.P. Box and N.R. Draper, Evolutionary Operation: A Statistical Method for Process Improvement, John Wiley & Sons, Inc., 1969 26. W.G. Hunter and J.R. Kittrell, "Evolutionary Operation: A Review," Technometrics, Vol 8 (No. 3), Aug 1966, p 389-397 27. Epstein and Sobel, Life Testing, J. American Statistical Association, Vol 48 (No. 263), Sept 1953 28. E. Rabinowicz, R.H. McEntire, and R. Shiralkar, "A Technique for Accelerated Life Testing," Paper 70- Prod-10, American Society of Mechanical Engineers, April 1970 29. O.B. Abu Haraz and D.S. Ermer, Accelerated Life Tests for Refrigerator Components, Proceedings, Annual Reliability and Maintainability Symposium, IEEE, 1980, p 230-234 30. J.C. Conover, H.R. Jaeckel, and W.J. Kippola, "Simulation of Field Loading in Fatigue Testing," Paper 660102, Society of Automotive Engineers, Jan 1966 31. B.A. Sayers, Human Factors and Decision Making: Their Influence on Safety and Reliability, Elsevie r Science Publishers, 1988 32. K.S. Park, Human Reliability, Elsevier Science Publishers, 1987 33. L.S. Mark, J.S. Warren, and R.L. Huston, Ed., Ergonomics and Human Factors, Springer- Verlag (New York), 1987 34. B.S. Dhillon, Human Reliability, Pergamon Press, 1986 35. J.J. Duane, Learning Curve Approach to Reliability Modeling, IEEE Transactions, Aerospace, 2, 1964, p 563-566 36. B.C. Spradlin, Reliability Growth Measurements Applied to ESS, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1986, p 97-100 37. E. Demko, True Reliability Growth Measurement, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1986, p 92-96 38. J.N. Bower, Reliability Growth During Flight Test, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1986, p 101-106 39. C.T. Gray, A Modelling Framework for Reliability Growth, Annual Reliability and Maintainab ility Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1986, p 107-114 40. L.H. Crow, On the Initial System Reliability, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1986, p 115-119 41. J.C. Wronka, Tracking of Reliability Growth in Early Development, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1988, p 238-242 42. L.H. Crow, Reliability Growth Estimation With Missing Data II, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1988, p 248-253 43. A.W. Benton and L.H. Crow, Integrated Reliability Growth Testing, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1989, p 160-166 44. D.B. Frank, A Corollary to Duane's Postulate on Reliability Growth, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1989, p 167-170 45. G.J. Gibson and L.H. Crow, Reliability Fix Effectiveness Factor Estimation, Annual Reliability and Maintainability Symposium (IEEE), Institute of Electrical and Electronics Engineers, 1989, p 171-177 Reliability in Design Charles O. Smith, Engineering Consultant Selected References • W.G. Ireson and G.F. Coombs, Ed., Handbook of Reliability Engineering and Management, McGraw- Hill Publishing Co., 1988 • D. Kececioglu, Reliability and Life Testing Handbook, Vol 1 and 2, Prentice-Hall, 1993 • D. Kececioglu, Reliability Handbook, Vol 1 and 2, Prentice-Hall, 1991 • L.M. Leemis, Reliability: Probabilistic Models and Statistical Methods, Prentice-Hall, 1995 • M.O. Locks, Reliability, Maintainability, and Availability Assessment, 2nd ed., ASQC, 1995 • Proceedings, Annual Reliability and Maintainability Symposium, Institute of Electrical and Electronics Engineers • P.A. Tobias and D.C. Trindade, Applied Reliability, 2nd ed., Van Nostrand Reinhold, 1995 Life-Cycle Engineering and Design ASM International Materials Life-Cycle Analysis Committee * Introduction ENVIRONMENTAL CONSIDERATIONS play an increasingly important role in design and development efforts of many industries. "Cradle to grave" assessments are being used not only by product designers and manufacturers, but also by product users (and environmentalists) to consider the relative merits of various available products and to improve the environmental acceptability of products. Life-cycle engineering is a part-, system-, or process-related tool for the investigation of environmental parameters based on technical and economic measures. This article focuses on life-cycle engineering as a method for evaluating impacts, but it should be noted that similar techniques can be used to analyze the life-cycle costs of products (see the article "Techno-Economic Issues in Materials Selection" in this Volume). Products and services cause different environmental problems during the different stages of their life cycle. Improving the environmental performance of products may require that industry implement engineering, process, and material changes. However a positive change in one environmental aspect of a product (such as recyclability) can influence other aspects negatively (such as energy usage). Therefore a methodology is required to assess trade-offs incurred in making changes. This method is called life-cycle analysis or assessment (LCA). Life-cycle analysis aims at identifying improvement possibilities of the environmental behavior of systems under consideration by designers and manufacturers. The whole life cycle of a system has to be considered. Therefore it is necessary to systematically collect and interpret material and energy flows for all relevant main and auxiliary processes (Fig. 1). Fig. 1 Factors considered in the life-cycle engineering approach. Source: Ref 1 Life-cycle analysis methods have been developed by governmental, industrial, academic, and environmental professionals in both North America and Europe. Technical documents on conducting LCA have been published by the Society of Environmental Toxicology and Chemistry (SETAC), the U.S. Environmental Protection Agency (EPA), the Canadian Standards Association (CSA), the Society for the Promotion of LCA Development (SPOLD), and various practitioners. For meaningful comparisons of the life-cycle performance of competing and/or evolving product systems, it is important that associated LCAs be conducted consistently, using the same standards. Although the common methodologies developed by SETAC, EPA, CSA, and SPOLD are a step in that direction, a broad-based international standard is needed. Such an effort is being undertaken by ISO 14000 series (TC207). Life-cycle thinking and techniques can be applied to products, processes or systems in various ways: it can help assess life-cycle economic costs (LCA econ ), social costs (LCA soc ) or environmental costs (LCA env ). A primary objective of LCA is to provide a total life-cycle "big-picture" view of the interactions of a human activity (manufacturing of a product) with the environment. Other major goals are to provide greater insight into the overall environmental consequences of industrial activities and to provide decision makers with a quantitative assessment of the environmental consequences of an activity. Such an assessment permits the identification of opportunities for environmental improvement. Acknowledgements Portions of this article were adapted from Ref 1 and 2. The authors wish to thank Sustainability Ltd. (United Kingdom) and the Secretariat of SPOLD (Belgium) for allowing the use of some of their information. References 1. M. Harsch et al., Life-Cycle Assessment, Adv. Mater. Proc., June 1996, p 43-46 2. J.L. Sullivan and S.B. Young, Life Cycle Analysis/Assessment, Adv. Mater. Proc., Feb 1995, p 37-40 Note * This article was prepared by Hans H. Portisch, Krupp VDM Austria GmbH (Committee Chair), with contributions from Steven B. Young, Trent University; John L. Sullivan, Ford Motor Company; Matthias Harsch, Manfred Schuckert, and Peter Eyerer, IKP, University of Stuttgart; and Konrad Saur, PE Product Engineering Life-Cycle Engineering and Design ASM International Materials Life-Cycle Analysis Committee * Life-Cycle Analysis Process Steps Life-cycle analysis is a four-step process; each of these steps is described in detail below. The process starts with a definition of the goal and scope of the project; because LCAs usually require extensive resources and time, this first step limits the study to a manageable and practical scope. In the following steps of the study, the environmental burdens (including both consumed energy and resources, as well as generated wastes) associated with a particular product or process are quantitatively inventoried, the environmental impacts of those burdens are assessed, and opportunities to reduce the impacts are identified. All aspects of the life cycle of the product are considered, including raw-material extraction from the earth, product manufacture, use, recycling, and disposal. In practice, the four steps of an LCA are usually iterative (Fig. 2). Step 1: Goal Definition and Scoping. In the goal definition and scoping stage, the purposes of a study are clearly defined. Subsequently, the scope of the study is developed, which defines the system and its boundaries, the assumptions, and the data requirements needed to satisfy the study purpose. For reasons of economy and brevity, the depth and breadth of the study is adjusted, as required, to address issues regarding the study purpose. Goal definition and project scope may need to be adjusted periodically throughout the course of a study, particularly as the model is refined and data are collected. Also during this stage, the functional unit is defined. This is an important concept because it defines the performance of a product in measured practical units and acts as a basis for product system analysis and comparison to competing products. For example, the carrying capacity of a grocery bag might be a sensible functional unit. Finally, the quality of the life-cycle data must be assessed in order to establish their accuracy and reliability. Typically, factors such as data age, content, accuracy, and variation need to be determined. Clearly, data quality affects the level of confidence in decisions that are based on study results. Step 2: Inventory Analysis. The second stage of LCA is a life-cycle inventory (LCI). It is in this stage that the various inputs and outputs (energy, wastes, resources) are quantified for each phase of the life cycle. As depicted in Fig. 3, systems boundaries are defined in such a way that the various stages of the life cycle of a product can be identified. The separation of burdens (inputs and outputs) for each stage facilitates improvement analysis. Fig. 3 Generalized system boundaries for a life-cycle inventory of a generic product. Source: Ref 2 For the purposes of LCI, a "product" should be more correctly designated as a "product system." First, the system is represented by a flowchart that includes all required processes: extracting raw materials, forming them into the product, using the resulting product, and disposing of and/or recycling it. The flowchart is particularly helpful in identifying primary and ancillary materials (such as pallets and glues) that are required for the system. Also identified are the sources Fig. 2 The life-cycle assessment triangle. Source: Ref 2 of energy, such as coal, oil, gas, or electricity. Feedstock energies, which are defined as carbonaceous materials not used as fuel, are also reported. After system definition and materials and energy identification, data are collected and model calculations performed. The output of an LCI is typically presented in the form of an inventory table (an example is shown in Table 1), accompanied by statements regarding the effects of data variability, uncertainty, and gaps. Allocation procedures pertaining to co- product generation, recycling, and waste treatment processes are clearly explained. Table 1 Example of a life-cycle inventory for an unspecified product Amount Inputs Energy from fuels, MJ Coal 2.75 Oil 3.07 Gas 11.53 Hydro 0.46 Nuclear 1.53 Other 0.14 Total 19.48 Energy from feedstocks, MJ Coal <0.01 Oil 32.75 Gas 33.59 Other <0.01 Total feedstock 66.35 Total energy input, MJ 85.83 Raw materials, mg Iron ore 200 Limestone 150 Water 18 × 10 6 Bauxite 300 Sodium chloride 7,000 Clay 20 Ferromanganese <1 Outputs Air emissions, mg Dust 2,000 Carbon monoxide 800 Carbon dioxide 11 × 10 5 Sulfur oxides 7,000 Nitrogen oxides 11,000 Hydrogen chloride 60 Hydrogen fluoride 1 Hydrocarbons 21,000 Aldehydes 5 Other organics 5 Metals 1 Hydrogen 1 Solid wastes, mg Mineral waste 3,100 Industrial waste 22,000 Slags and ash 7,000 Toxic chemicals 70 Nontoxic chemicals 2,000 Water effluents, mg COD 1,000 BOD 150 Acid, as H + 75 Nitrates 5 Metals 300 Ammonium ions 5 Chloride ions 120 Dissolved organics 20 Suspended solids 400 Oil 100 Hydrocarbons 100 [...]... before the product reaches the user Utilize Standard, Proven Parts (Ideally, Proven Commercial Parts) Whenever Possible If standard parts cannot be used, use parts from standard, proven manufacturing processes and proven existing quality control procedures and equipment If newly designed parts are required, the less the new design departs from existing designs, the less chance there will be for problems... Mater Proc., June 1996, p 43- 46 Life-Cycle Engineering and Design ASM International Materials Life-Cycle Analysis Committee* Conclusions Life-cycle engineering in particular, life-cycle assessment is gaining importance for design and materials engineers because environmental considerations are increasingly important factors in design and materials selection The creation and development of environmental... fixtures and will help ensure that parts are assembled correctly Design parts so that access to them in the product and vision of them is unobstructed (Ref 4) (This is a design for service guideline as well.) This will promote correct assembly and will help verify that it is correct It will facilitate testing and replacement of parts, if necessary References cited in this section 1 D.M Anderson, Design. .. calculated A standard list covers the following themes, which are more or less identical with most of the approaches taken in LCA literature: • • • • Global criteria: Resource use (energy carriers and mineral resources, both renewable and nonrenewable, and water and land use), global warming, ozone depletion, and release of persistent toxic substances Regional criteria: Acidification and landfill demand Local... defined and that they are equivalent Table 2 shows the materials and weights of the four different fender designs Table 2 Material and weight of the different fender designs Material Thickness Weight mm in kg lb Steel 0.7 0.0275 5.60 12 .35 Sheet molding compound 2.5 0.10 4.97 11.00 Polyphenylene oxide/polyamide 3. 2 0.125 3. 35 7.40 Source: Ref 1 Data Origin and Collection Data in this context means all pieces... Engineering and Design ASM International Materials Life-Cycle Analysis Committee* References 1 M Harsch et al., Life-Cycle Assessment, Adv Mater Proc., June 1996, p 43- 46 2 J.L Sullivan and S.B Young, Life Cycle Analysis/Assessment, Adv Mater Proc., Feb 1995, p 37 -40 3 "Guidelines for Life Cycle Assessment: A Code of Practice," Society of Environmental Toxicology and Chemistry (SETAC), Europe (Brussels), 19 93. .. Stamatis, TQM Engineering Handbook, Marcel Dekker, 1997 Using Quality Tools in DFM, Tool and Manufacturing Engineers Handbook, Vol 6, Design for Manufacturability, Society of Manufacturing Engineers, 1992 9 J.M Juran, Juran on Planning for Quality, Macmillan, 1988 10 Brown, Hale, and Parnaby, An Integrated Approach to Quality Engineering in Support of Design for Manufacture, Chap 3. 3, Design for Manufacture:... components and designs Failure to make the product design simple enough, for example, failure to make the product easy to assemble, potentially leading to assembly and adjustment errors Design for Quality James G Bralla, Manufacturing Consultant Evaluating a Product Design for Quality Granted that design is a major determinant of product quality, how does the designer evaluate a prospective design to... data on assembly as well as individual parts quality He has analyzed factors that can result in assembly errors, even if the parts assembled do not have defects; for example, part misalignments, misplaced or missing parts, or part interferences His system is designed to aid the designer in evaluating the potential quality of particular configurations before the design is finalized Fig 1 Summary of... of processes and materials Such information includes material and energy flows of processes, process descriptions, materials and tools, suppliers, local energy supply, local energy production, production and use of secondary energy carriers (e.g., pressurized air, steam), and location of plants Which processes are the most relevant and must be considered in more detail depends on the goal and scope of . Factorial Designs, Technometrics: Part I, Vol 3 (No. 3) , Aug 1961, p 31 1 -35 1; Part II, Vol 3 (No. 4), Nov 1961, p 449-458 22. G.E.P. Box, N.R. Draper, and J.S. Hunter, Empirical Model-Building and. Technometrics, Vol 8 (No. 3) , Aug 1966, p 38 9 -39 7 27. Epstein and Sobel, Life Testing, J. American Statistical Association, Vol 48 (No. 2 63) , Sept 19 53 28. E. Rabinowicz, R.H. McEntire, and R. Shiralkar,. Oil 3. 07 Gas 11. 53 Hydro 0.46 Nuclear 1. 53 Other 0.14 Total 19.48 Energy from feedstocks, MJ Coal <0.01 Oil 32 .75 Gas 33 .59 Other <0.01 Total feedstock 66 .35 Total