モノづくりにおけるシステム設計最適化

At the start of my Ph.D. in 1980, I caught a glimpse, purely by chance, of the emerging field of computer-aided design (CAD). It intrigued and fascinated me to such an extent that I ended up scrapping my original plans, switching schools and changing my research area. Even though my new school, Ohio State, was one of only a handful of schools with computing facilities dedicated to CAD, I ran into stiff resistance when I expressed my desire to get a Ph.D. in CAD. I was told that CAD was hardly an intellectually challenging field worthy of a Ph.D. dissertation. I was directed to consider mainstream mechanical engineering areas, such as solid mechanics, vibrations, kinematics, and dynamics. The closest I could get to CAD was to do my dissertation in FEA, which allowed me to do at least part of my work in computing and visualization.When I began my academic career at Arizona State, I thought I was finally free to pursue my true love. But I soon realized that we were still a fringe group; faculty in traditional fields, such as thermofluids and solid mechanics, took a dim view of computational research. The proposed thesis plan for my first graduate student (Expert System for Conceptual Synthesis of Frame Structures) was rejected by the Graduate Chair, who remarked “This is not mechanical engineering.” He viewed it as purely a computer program without any regard for the fact that we needed to explicate, structure, and represent experiential knowledge for structural synthesis not found in any textbook on the subject.Of course, I was not alone in facing this predicament. Fortunately, for misfits like us there was an ASME Division that welcomed us. Originally named the Computer Engineering Division (CED), and later known as Computer & Information Engineering (CIE) Division, it was approved in 1979 and began operating in 1980. Unlike academia, industry was well aware of the potential of computing and information technologies to revolutionize product design and manufacturing. Visionaries from computer industry (CDC, IBM, DEC, Applicon), an infant software industry (SDRC, CV, Swanson), and a variety of OEMs (GM, GE, McDonnell-Douglas) led a grassroots effort to convince ASME of the importance of mechanical engineers active participation in these evolving areas through the creation of a new Division. The first CED newsletter in 1981 boldly heralds “…the dawn of an era that is certain to be dominated by computer technology. All projections indicate that mechanical engineers, more than any other professional group, will be more involved in the utilization of this (computer) technology.” They saw MEs playing as important a role in the IT revolution as their far predecessors had in the industrial revolution—a prediction that was to come true.Prof. Ali Seirig was appointed the first Chair of CED. I am in awe of the progress this new Division made in just the first two years. Twenty-four technical committees were set up and an annual conference was initiated in 1981. This conference was unique in that it was associated with an exhibition of the latest hardware and software from leading vendors. This element was critical in keeping the ASME community well informed about the current state of engineering computing. It is, therefore, not surprising to see that this Division was heavily industry dominated—21 out of 24 Technical Committee Chairs were from industry. Sadly, today industry participation in CIE has sagged. Did CIE change because industry participation diminished, or did industry reduce its participation because CIE became less relevant to their needs? We can only speculate about the reasons.CED soon became the fastest growing Division within ASME. The CED/CIE conference and exhibition attracted participants from a wide range of areas, not just CAD/CAM and FEA but kinematics, robotics, heat transfer, and fluid mechanics. This diverse community only had one thing in common, the application of computational methods to problems in their respective fields. As traditional conferences and journals gradually came around to seeing computational methods as valuable contributions in their own fields, they became more accepting of papers of this nature. Thus began the return of computational researchers back to their own discipline communities, shrinking the size of CIE conferences. Finally, in 1994, the CIE conference was colocated with Design Engineering Technical Conferences (DETC).The founders of CED debated the type of journal they needed to have. They felt that given the rapid evolution of computing technologies, an archival journal like an ASME Transactions was not appropriate. At the same time, they wanted their journal to be more technical than a trade magazine. They ended up creating a “hybrid” quarterly publication called CIME (Computers in Mechanical Engineering), with Ali Seirig as its editor. This magazine was produced in full color and was very informative about the latest developments in engineering software. In the words of the editor, CIME was “user-oriented” not “research oriented.” Unfortunately, this philosophy did not command much respect in academia and eventually CIME was merged into ASME’s monthly magazine Mechanical Engineering.And so it came to be that unlike all other ASME conferences and Divisions, CIE did not have any associated journal. Over the years, CIE leaders made several attempts at getting a Transactions journal approved, but to no avail. Reasons for rejection ranged from “computing technologies have no archival value” to the failure to sustain CIME magazine.In 2000, a small group of CIE Division “activists” decided to make another push for a journal. Yong Se Kim, David Lee, Simon Szykman, and David Rosen were the principals in this effort. They came up with a strategy based on lessons from past failures. That included building alliances with three other Divisions (Design, Manufacturing, and Systems & Controls), and demonstrating that an editorial board could be formed with well known researchers who had extensive publication records. I became aware of this effort when I received a call out of the blue, asking me the intriguing question “How would you like to be the Chief Editor of an ASME Transactions?” Of course, the very next sentence brought me down to earth quickly “…the problem is that the journal doesn’t yet exist – will you help us get it approved by ASME?” Thus began my involvement with this journal. We put together an impressive editorial board that included two NAE members and research leaders in each of our targeted areas. Phil Divitero, ASME Director of Publications, immediately saw the marketing potential of this journal, and became a key ally. Bahram Ravani, DED Chair, gave valuable advice on writing our proposal to ASME. Art Erdman, himself a CIE pioneer, happened to be the Chair of ASME Publication Committee, which had authority of approving new journals, which gave us a much needed sympathetic ear on the committee to make our case. In a café in Chicago, before our presentation, we brainstormed various names for the journal and settled on Journal of Computing & Information Science in Engineering (JCISE). The journal was approved and began publishing in the first year of the new millennium, 2001. The CIE Division finally had an archival journal of its own with three cosponsoring Divisions. In 2005, after much lobbying and deliberation, the Design Engineering Division became an equal partner with CIE—an important step in going mainstream.From the very beginning we decided to focus sharply on computational methods for mechanical product development. This set us apart from journals from private publishers that accepted everything and anything related to computing—from gaming to geology, from biology to every branch of engineering. We did not want to dilute our journal with such a wide and general scope. We stipulated that every paper submitted to JCISE must demonstrate applications of its techniques to mechanical design, mechanical analysis, product manufacturing, or quality assurance. Through several iterations we settled on eight major categories to include within the scope of our journal: solid modeling (including parametrics), computational geometry (including reverse engineering), computational metrology (including CMM and tolerance modeling), haptics and virtual reality, engineering informatics, simulation (including FEA, meshing, and optimization), AI/Knowledge based systems, and computer aided manufacturing. Given the practical nature of our field, we also decided to publish papers along two tracks: Research and Application. The latter has subcategories of Software Reviews, Technology Reviews, Tech Notes, and Industry Pilot Projects. The idea was to keep the journal relevant to industry as well as academia. We instituted a three-level rigorous review process for appointment of Associate Editors. We owe it to the founding editorial board for setting sound policies that resulted in quick recognition of JCISE as an archival publication of high quality. That group consisted of Paul Wright, David Rosen, Nick Patrikalakis, Deba Dutta, Susan Urban, Martti Mantyla, Dana Nau, S. Jayaram, Pradeep Khosla, Harry Cheng, and Ravi Rangan. Since we see ourselves as being at the intersection of computer science and mechanical engineering, it was appropriate to have about half of the AEs from each field, and we managed to do so.ACM (Association for Computing Machinery) approached us in 2001 to become an official cosponsor—an offer we gladly accepted in order to strengthen the linkage with our computer science colleagues. From 2001 to 2004, we published a special issue annually drawn from the best papers of the ACM Solid Modeling conferences. Unfortunately, this conference series became too broad, and it was difficult to accommodate their best papers in JCISE without violating our objective of serving the engineering community; this annual tradition of ACM special issues had to be discontinued.ISI included JCISE in its data collection in 2004; after 3 years of this process, the first Impact Factors for JCISE became available in 2007 (for the 2004–2006 period). With respect to ISI Impact Factors, JCISE ranks in the top third of all ASME Transactions; it is better than many long established journals in CAD/CAM and AI areas. Our Impact Factor has continued to improve each year. How meaningful are such statistics in gauging the quality of a journal is debatable. More meaningful metrics are in the offing and we hope they will supplant bean counters of today.When we opened shop in 2000, ASME did not have any web based tool for paper submission and review management. Being the journal focused on computing and information science, we refused to conduct paper reviews the old fashioned way and began developing eLane. With the help of one of our associate editors, Susan Urban, a database expert, and one of her brilliant students, Anish Shah (no relation), we designed and implemented eLane over a period of 3 years. For the past 10 years, we have hosted, maintained, and continuously improved eLane to support not only JCISE but also other journals, such as Research in Engineering Design, and CIE, DTM, and NSF Grantees conferences. eLane blazed a new trail and guided ASME to develop its own “Journal Tool.” Data security and confidentiality is a critical issue in online systems. I am particularly indebted to one of our founding associate editors, Simon Szykman, who provided valuable advice on security aspects of the system by constantly trying to enter the system through unintended holes. It is no surprise that Simon went on to become the first Director of the Cyber-Security group at US Department of Homeland Security and is now the CIO of the Department of Commerce.With Bahram Ravani taking over as the new chief editor of JCISE, we have begun the process of gradually migrating from eLane to ASME’s Journal Tool. Although the Journal Tool still lacks some functionality available in eLane, the reasons for migration are that this will provide greater visibility to JCISE through ASME websites, set JCISE at par with other Transactions, make it easier to transfer papers between ASME journals and, most importantly, have 24/7 support from ASME’s IT professionals.My tenure as chief editor is ending as it started, with a special issue providing snapshots of each of the technology areas within our scope. In both cases, I put together a wish list of papers and expert groups to co-author the state of art reviews. I had hoped to have every area covered, but some papers did not materialize this time around. Nevertheless, this special issue will be a good reference for most, if not all of the areas JCISE covers. For V1 N1, I invited each of our founding Associate Editors to write state-of-the-art surveys of their fields in collaboration with other experts in their respective areas. This special issue contains survey papers not only in some well-established CIE areas but also in a few emerging fields.Computational methods and information technologies related to engineering product development have come a long way. CAD, CAM, FEA, CFD, VR, Reverse Engineering, Computational Metrology, Optimization, and many other simulation techniques are now pervasive in industry. Even traditional fields, such as thermal science, fluid mechanics, and solid mechanics, have embraced numerical methods and computer visualization. What started on the fringes is now the mainstream. We owe it to the founders of the CED/CIE Division who saw this potential more than 30 years ago. Let us recognize Ali Seireg (Wisconsin), J. Callahan (McDonnell Douglas), V. Tipnis, T. Shoup (Santa Clara), D. Dietrich (Swanson), L. Hulbert (Battelle), E. Heer (NASA), S. Rhode (GM), R. Fulton (Georgia Tech), J.Cokonis (GE), R. Arvikar (Bell Labs), J. Lemon (SDRC), D. Riley (U. Minnesota), and R. Raghavan (Foster Wheeler).A high quality archival journal is extremely important to any research community. A conference alone cannot be sufficient. Conferences, at least in engineering, serve the purpose of quick dissemination of work in progress. Having an archival journal aids the maturation of a research community. Not all conference papers are suitable for archival in a journal. An additional complication in computing and IT is the rapid rate of development and consequent obsolescence of ideas and methods. What then should we archive? There certainly are many techniques in our field that have withstood the test of time. B-Rep solid models, B-splines, and NURBS, regularized Boolean algorithms, Attributed Adjacency Graph based feature recognition, and bipartite graphs for constraint solving are but a few examples. But most research is incremental, and it is important to archive snapshots of major milestones in each area. NURBS did not just come about suddenly. There were B-splines, rational B-splines before the idea of nonuniform knot spacing.JCISE associate editors serve 3 year terms, renewable for an additional 3. In addition to the founding group of AEs, I want to take this opportunity to thank all our current and past AEs. They are the ones that do the bulk of the work and get the credit for maintaining our high quality. I am very grateful to the following individuals: J. Michopoulos, K. Saitou, A. Goel, I. Grosse, K. Law, X. Qian, J. Oliver, S. McMains, S. Gao, A. Fischer, J. Vandenbrande, C. Geiger, Y. Kitamura, C. McMahon, A. Joneja, S. K. Gupta, R. Crawford, K. Lee, J. Corney, N. Dorighi, L. Joskowicz, and S. Callahan.I am sure that our new chief editor, Bahram Ravani, will take JCISE to new heights. My very best wishes to JCISE readers, authors, and reviewers. For me, this has been a labor of love.

The shortcomings of the existing approach to assessment of manufacturability of a product design (PD), which determines production, operational and repair manufacturability and does not take into account the manufacturability of the product's disposal. It is proposed to use coefficients when assessing manufacturability that take into account the simultaneous influence of the PD characteristics on the labor intensity of manufacturing, operation, repair and disposal of the product. Keywords product design, manufacturability, manufacturing, operation, repair, disposal, coefficient, labor intensity aleks146@mail.ru

Highly accelerated life testing has been heavily promoted at Sandia (and elsewhere) as a means to rapidly identify product weaknesses caused by flaws in the product's design or manufacturing process. During product development, a small number of units are forced to fail at high stress. The failed units are then examined to determine the root causes of failure. The identification of the root causes of product failures exposed by highly accelerated life testing can instigate changes to the product's design and/or manufacturing process that result in a product with increased reliability. It is widely viewed that this qualitative use of highly accelerated life testing (often associated with the acronym HALT) can be useful. However, highly accelerated life testing has also been proposed as a quantitative means for "demonstrating" the reliability of a product where unreliability is associated with loss of margin via an identified and dominating failure mechanism. It is assumed that the dominant failure mechanism can be accelerated by changing the level of a stress factor that is assumed to be related to the dominant failure mode. In extreme cases, a minimal number of units (often from a pre-production lot) are subjected to a single highly accelerated stress relative to normal use. If no (or, sufficiently few) units fail at this high stress level, some might claim that a certain level of reliability has been demonstrated (relative to normal use conditions). Underlying this claim are assumptions regarding the level of knowledge associated with the relationship between the stress level and the probability of failure. The primary purpose of this document is to discuss (from a statistical perspective) the efficacy of using accelerated life testing protocols (and, in particular, "highly accelerated" protocols) to make quantitative inferences concerning the performance of a product (e.g., reliability) when in fact there is lack-of-knowledge and uncertainty concerning the assumed relationship between the stress level and performance. In addition, this document contains recommendations for conducting more informative accelerated tests.

The Cambridge Engineering Selector (CES) is a tool that focuses on material, process, and shape combinations of product design. The Resource Consumption Model (RCM) is a tool that focuses on production process resources, resource costs, production volume, production capacity, and manufacturing cycle time. Both tools help identify viable manufacturing process alternatives to meet stated manufacturing objectives.

The fields of design and engineering both contribute to product design and development. Increasingly design teams require an integrated approach in environments where mutual understanding and respect replace traditional professional rivalries. These new synergies both enhance communication and understanding between designers and engineers and lead engineering into new areas of professional activity. Engineers are integral to the product development process, but change in product development and manufacturing requires new responsibilities; design engineers must assume a greater role to achieve successful product realisation. However, to be effective engineers must develop new skills; creative design ability, understanding of societal and environmental impacts and a human-centred approach. These themes, not typically addressed by engineering curricula are evident in a new approach to engineering education - product design engineering. This chapter addresses issues confronting product design and development and examines the emergence of this new engineering professional in response.

Gap Analysis and Optimization of Process Involved in Product Design and Development by Integrating Enterprise Resource Planning & Product Lifecycle Management

Presently, materials security and production of environmentally conscious materials (ecomaterials)1) are of concern to the global community, which needs to recognize the challenges that both present. As a nation, Japan has focused on better management of natural resources and materials, and has developed a framework to advance a move towards a closed-loop economy through advancing and implementation of its knowledge of the 3Rs (reduce, reuse, recycle). Ecomaterials also make an important role in ecodesign. Ecodesign is an approach to design of a product with special consideration for the environmental impacts of the product during its whole lifecycle. Substantial progress has been made in ecodesign and high-performance fabrication for sectors such as living, automotive, electrical, machinery, building, etc., where a need to improve resource productivity and adopt ecomaterials are a key priority for progress.2) The concept of ecomaterials, defined as an ecosphere with three basic paths (i.e., frontier, environmental protection, and amenity), was originally proposed in Japan in 1992 and became the preferred area of focus in materials engineering through the 1990s.1) In the beginning of the 21st century, Halada et al.3) attempted to classify ecomaterials into three categories as follows: (1) Functional materials for environmental protection, (2) Energy-saving materials and materials supporting lowemission systems, and (3) Materials designed by means of life-cycle assessment or analysis (LCA), and selected based on a lower environmental impact. This is why not only materials selection is important, but also novel process technologies for synthesizing high-performance materials with a low environmental burden. Both are also dependent on product design to achieve coexistence of societal economic health and reduced environmental burden. Therefore, general guidelines for ecomaterial selection and development were discussed and proposed,2) in which ecoefficiency was defined by an equation.4) We have developed and standardized the indices of this equation, and its framework for disclosing information on environmental impact of materials traded under international collaboration.5) The six environmental information indices are demonstrated in the eco-star system.6) The specific challenges facing ecomaterials have played an important role in the global recognition of environmentally conscious concepts since 1993, and have served motivators for the development of an eco-friendly world. In fact, the ecomaterials concept has already been widely accepted in the fields of material production and product manufacturing, in addition to being accepted by the academia and various governments. This is especially true in Japan, where adoption of ecomaterials that are less hazardous, or have a higher resource productivity, has noticeably increased. Despite all the importance attached to ecomaterials, its concept has now become outdated, and a new categorization of ecomaterials is therefore being sought. Through the declaration at Ishigakijima,7) and at the round table conference at ICEM9,8) we have discussed the breakdown and rebuilding of the ecomaterials concept for a sustainable society. The point at issue, and the direction of technological advancement of the world, has remained confused, and it is this that we seek to correct. Moving from high eco-efficiency of products to consumer orientation and regional community adaptation is focused upon as a part of the “amenity”, one of three basic paths in achieving an ecosphere. A new concept, the robust design of materials, is also proposed as part of new range of activities focused on ecomaterials.

Even though knowledge management has been a subject of research for a long time, management of through-life engineering service knowledge (SK) has started getting more attention quite recently. With the help of literature review and analysis, this paper identifies possible drivers to extend the product life cycle, presents definitions of ‘knowledge’ and ‘engineering service knowledge’ and identifies research gaps and challenges in digital feedback of through-life engineering SK to product design and manufacture. The paper presents a causal loop model to represent causes and effects of through-life engineering SK on product design and manufacture. A digital framework is presented to address integration challenges in digital feedback of through-life engineering SK to product design and manufacture. The digital framework is developed with the intention of developing a SK backbone demonstrator application. Industrial experts have validated the initial framework. Detailed case studies shall be undertaken to enhance this framework in future.

Through past decade, the complexity of integrated product development process has been significantly increased, due to highly elaborated customer’s needs, market requirements and their multi-disciplinary nature. In this context, the meaning and formal structure of such information must be well managed since initial stages of product development, in order to avoid semantic heterogeneity and subsequent mistakes in interpretation. The aim of this paper is to understand the current issues related to this scenario, through the study of later works and research regarding Semantic Interoperability through ontologies in multiple domains, applicable in the field of Product Development and Manufacturing. Search material points out that a significant issue regards the input of information, since most of current models merely translate information from different sources, instead of understanding its nature and stablish a common standard to extract and structure it. Research has suggested that Knowledge Extraction models may be a viable path to filter and refine the quality of the input information, as means to improve the accuracy and effectiveness of new knowledge. This research structured its findings in a model that explores the issues of semantic interoperability through reference ontologies, to bring light to new research themes, validated through further research.

There have been a considerable amount of interests in providing the state-of-theart product design and manufacture techniques and methods accessible on the Internet from web browsers. This chapter concerns with the process of building web applications for product design and manufacture. The focus is on how such systems are being developed and implemented. However, there have been considerable difficulties in the design, development, and implementation of web applications in product design and manufacture. The complexity can be understood in several ways. For example, there is no rigorous and systematic approach to the development of web applications at present. Current web application development and management practices are mostly ad hoc, heavily dependent on the knowledge and experience of individual developers.

Globalised demands for products variants with reduced developmental time lead firms to consider effective and organised product development approach. In order to fulfil these requirements, manufacturing firms are increasingly moving towards platform-oriented product development or are planning to do so to reduce complexity and better leverage investments in product design, manufacturing and marketing. In this paper, an overview of key topics related to platform design and product variety management is provided. A review of recent works on product platform design and its application to industries is discussed. A generic design structure matrix (DSM) tool is presented that outlines an effective methodology for platform design. This methodology is explained through presenting an example of a diesel fueled ship engine. Different limitations and risks associated with the management of platform-based product design and development are discussed along with some future research directions too.

Introduction and Overview Products and Product Quality Product Warranty Warranty Management Systems Approach to Warranty Management The Role and Use of Data in Warranty Management Warranty Cost Analysis Warranty Considerations in Product Design and Development Implications of Warranty on Production Decisions The Role of Warranty in Marketing Warranty Logistics Reliability Improvement Warranties Financial, Societal, and Legal Aspects of Warranty Warranty Management System Epilogue

Chapter 34 The Value Chain: A Study of the Durable Medical Equipment Industry

In order to obtain product designs that maximize their appeal to customers, a concurrent product design method is proposed in which aesthetic factors are implemented during conventional product design. Aesthetic attributes, which are a subset of subjective attributes, are evaluated concurrently with analytically obtained objective attributes of the product's characteristics. The interaction of these aesthetic and objective attributes, as it relates to the product's utility and manufacturing cost, is clarified. Ultimately, the solution that has the minimum ratio of manufactured cost relative to the customer's expected product price is selected as the optimum design solution. Applied examples pertaining to robot designs are given, to demonstrate these methodologies.

During the New Product Development (NPD) cycle, it is important to focus and integrate relevant information into the stages of product conceptualisation, design and development so that they can be used for product and process design effectively. In this paper, a Generic Product and Process Development System (GPDS), which integrates knowledge-based technologies of Rule-Based Expert System (RBES) and Case-Based Reasoning (CBR), is proposed to facilitate product and process development. Although RBES is adopted for sorting product design criteria, relevant past cases are retrieved by the CBR system during product and process design stages. In doing so, previous knowledge in terms of rules and past practices will be made use of during the product and process design stages, resulting in an enhancement of the efficiency of design and operations. By applying GPDS in Hasbro Fast East Limited, the new product design life cycle is greatly shortened with significant reduction in the total development cost.