Performing Changes in Product Development: A Framework with Keys for Industrial Application

Industrial product development requires continuous improvements in work procedures as a result of constantly changing demands. Support tools have proven to be an oft chosen way to meet new demands; however, few research efforts have been made in how to implement new tools. This article is a contribution to knowledge on carrying out the implementation of support tools. The basis consists of four field studies performed during 1994–1999, containing 78 qualitative research interviews and focusing on the implementation and use of different support tools. A re-analysis has been performed of selected interviews from the field studies, in total 30 interviews. This resulted in recommendations for an implementation framework, consisting of an Implementation Cycle, Organizational Change Field and Managerial Consistence, and five implementation keys: Goal setting, Kowledge Development, Anchoring at All Levels, Suitable Resources and Focus on the Individual.     

CADOM: A Component Agent-based Design-Oriented Model for Collaborative Design

Information technology is the foundation for collaborative design. This paper reviews the state-of-the-art of the current research on product modeling, and a schema for a Design-Oriented Model (DOM) containing functional, structural and management data is proposed. The functional data explains the design purpose, function, object behavior and design rationale; the management data is for keeping the consistency of the model data, capturing the evolution process and controlling the operation action and authority; the structural data is the core of the model data. The integration of functional and management data directs the model towards design integration in place of application integration. The modeling system adopts the Component Agent (CA) mechanism that represents a complex product in an intelligent, autonomous hierarchy. A CA encapsulates the DOM data and consists of a definer, a communicator, an adaptor and a manager. These units are responsible for defining the model data, interacting with other agents, deriving special data and managing the constraints, version, authority and operation. Finally, several aspect supporting the collaborative design enabled by the CADOM (CA-based DOM) are discussed, as the multi-views model, the semantics communication between perspectives, the dynamic constraints management, the version and authority management, and the product and process integration. The discussion indicate that the model is an information infrastructure with more capabilities for collaborative design.     

Functional Interdependence and Product Similarity Based on Customer Needs

In this paper, related product functions are determined for a group of approximately 70 consumer products. Using customer need data, a new matrix approach is introduced to identify these relationships. Techniques are then created for determining product similarity. These techniques are clarified and validated through three case studies, including beverage brewers and material-removal products. The results of these case studies are argued to have significant impact on design-by-analogy procedures, benchmarking methods, mass customization strategies and modular design. The paper concludes with a discussion of applications and related procedures for product development.     

Evaluation of Product and Process Design Robustness

Critical design decisions are commonly made throughout the product development process assuming known material and process behavior. However, stochastic variation during manufacture can inadvertently result in inferior or unacceptable product performance and reduced production yields. Stochastic simulations have been developed to estimate the end-use performance distribution prior to the commitment of hard tooling. This article proposes a definition for integrated product and process robustness, and extends existing stochastic methods to model the important role of the manufacturing flexibility in elimination of defects and product optimization. The goal is to enable the designer to understand and account for not only the negative effects of manufacturing variation, but also the positive impact of manufacturing flexibility wherein instantaneous corrections in the manufacturing process can frequently improve the product quality and eliminate flaws in the product design. Then, a methodology is introduced and contrasted with conventional development methods in the evaluation of best practices for development of a molded plastic component.     

A Taxonomy for Design Requirements from Corporate Customers

We have developed a taxonomy that classifies those needs of a corporation that impact product design. We call these needs corporate requirements. In contrast to the consumer or end-user requirements, corporate requirements come from internal sources such as marketing, finance, manufacturing, and service. This taxonomy allows for an organized method of gathering, managing, and retrieving the requirements. The taxonomy also helps to facilitate a broader, clearer form of Quality Function Deployment. Generic in nature, this taxonomy provides a template with which to create taxonomies for a given product within a given company or industry. We include an industrial case study to demonstrate this concept.     

A scheduling method for Berth and Quay cranes

This paper discusses a method for scheduling Berth and Quay cranes, which are critical resources in port container terminals. An integer programming model is formulated by considering various practical constraints. A two-phase solution procedure is suggested for solving the mathematical model. The first phase determines the Berthing position and time of each vessel as well as the number of cranes assigned to each vessel at each time segment. The subgradient optimization technique is applied to obtain a near-optimal solution of the first phase. In the second phase, a detailed schedule for each Quay crane is constructed based on the solution found from the first phase. The dynamic programming technique is applied to solve the problem of the second phase. A numerical experiment was conducted to test the performance of the suggested algorithms. RID="*" ID="*" This research has been supported in part by Brain Korea 21 Program (1999–2002). Correspondence to: Y.-M. Park     

Developing Strategic Alliances: A Framework for Collaborative Negotiation in Design

This work applies a theory-based framework of collaborative negotiation to some of the disputes that regularly arise during group design. Although the framework was developed to provide general support for group work, this paper focuses on its use as a design tool. The framework, embodied in our system NegotiationLens, has four facets. It: 1. Provides a negotiation method intended to produce gain for all parties. 2. Provides an efficient process for conflict resolution. 3. Develops working alliances. 4. Lets parties decide quickly when they should go their separate ways. The framework produces the above results by: • Helping parties develop well-reasoned and clearly articulated points of view (Adelson and Jordan, 1991; Conklin and Yakemovic, 1991; Conklin and Begeman, 1988; MacLean et al ., 1991). • Creating a context of committment and respect. • Moving negotiating parties away from an adversarial stance and into a collaboration. • Allowing joint construction of solutions that are more beneficial than the unilateral solutions each party initially brought to the table. We present our framework for collaborative negotiation, describe NegotiationLens, and present two cases in which it was used. We present a third case, a large design project with recurrent design conflicts, and argue how NegotiationLens could have been of benefit there.     

More than Just Robust Design: Why Product Development Organizations Still Contend with Variation and its Impact on Quality

Current market conditions require design and manufacturing companies to continually increase product functionality, reduce design cycles, decrease cost and improve quality. One way to improve quality is to minimize the impact part and process variation has on final product quality. Although companies know they must reduce variation, they are still struggling with executing coherent variation management strategies. To understand why companies still fail to systematically address variation, an ideal model of variation management is proposed, entitled Variation Risk Management (VRM). This model was used to assess the state of industry practice. These results are compared to the current literature available on the subject. It was found that many problems with industry implementation are due to a lack of quantitative models that enable a design team to make quick and accurate decisions. This paper concludes with a list of interesting challenges facing the VRM field.     

A Subjective Design Framework for Conceptual Design of Polymeric Processes with Multiple Parameters

Polymer processes are in general difficult to model, especially because of coupling between process conditions, polymeric behaviors and geometries. Arising from high thermal gradients, non-Newtonian viscous behaviors and non-linear pressure effects, polymer processing is not well described mathematically. A conceptual design methodology is proposed formally as a useful tool for treating polymeric processes with multiple performance parameters on a structured design platform. Without resorting to engineering models, this approach deals with the initial selection of process conditions within a three-stage framework: (1) qualitative design; (2) process modeling; and (3) quantitative design. Based on subjective reasoning, this procedure makes it possible to account for one’s prior experience, and incorporate it into the process development. The notion of conceptual robutstness is introduced to ensure deesign quality in the early-stage process development. A case study of compression molding is illustrated in a step-by-step manner.     

A computational study of LP-based heuristic algorithms for two-dimensional guillotine cutting stock problems

In this paper we develop and compare several heuristic methods for solving the general two-dimensional cutting stock problem. We follow the Gilmore-Gomory column generation scheme in which at each iteration a new cutting pattern is obtained as the solution of a subproblem on one stock sheet. For solving this subproblem, in addition to classical dynamic programming, we have developed three heuristic procedures of increasing complexity, based on GRASP and Tabu Search techniques, producing solutions differing in quality and in time requirements. In order to obtain integer solutions from the fractional solutions of the Gilmore-Gomory process, we compare three rounding procedures, rounding up, truncated branch and bound and the solution of a residual problem. We have coded and tested all the combinations of algorithms and rounding procedures. The computational results obtained on a set of randomly generated test problems show their relative efficiency and allow the potential user to choose from among them, according to the available computing time. Rceived: January 9, 2001 / Accepted: December 10, 2001     

A Study on Engineering History Base

During engineering processes, many kinds and amounts of information are used and produced. Such information is useful in successive cases, and thus its reuse is desired. In this paper, information on attributes of the products is referred to as ‘product information’, and information on the reasons for and/or history of a designer’s thought process is referred to as ‘process information’. According to this classification, process information can be used for obtaining an explanation of product information. The purpose of this work is to build a database, called an ‘engineering history base’, from which engineers can retrieve explanations to enable the reuse of product information. In this paper, explanation from the ‘process’ viewpoint is thought to be important in promoting the reuse of product information. There are two types of explanation for the process: teleological and causal. However, until now, little attention has been paid to the causal explanation for the process. Thus, in this paper, an information model which focuses on both types of explanation is proposed. The model is adopted for the engineering history base and a prototype system is developed. The appropriateness of this model is discussed by analyzing the actual data in the development of a color video printer.     

A survey and annotated bibliography of multiobjective combinatorial optimization

This paper provides a survey of the research in and an annotated bibliography of multiple objective combinatorial optimization, MOCO. We present a general formulation of MOCO problems, describe the main characteristics of MOCO problems, and review the main properties and theoretical results for these problems. The main parts of the paper are a section on the review of the available solution methodology, both exact and heuristic, and a section on the annotation of the existing literature in the field organized problem by problem. We conclude the paper by stating open questions and areas of future research. Received: February 7, 2000 / Accepted: April 14, 2000     

A Theory of Complexity, Periodicity and the Design Axioms

One of the topics that has received the attention of mathematicians, scientists and engineers is the notion of complexity. The subject is still being debated, as it lacks a common definition of complexity, concrete theories that can predict complex phenomena, and the mathematical tools that can deal with problems involving complexity. In axiomatic design, complexity is defined only when specific functional requirements or the exact nature of the query are defined. Complexity is defined as a measure of uncertainty in achieving a set of specific functions or functional requirements. Complexity is related to information, which is defined in terms of the probability of success of achieving the Functional Requirements (FRs). There are two classes of complexity: time-dependent complexity and time-independent complexity. There are two orthogonal components of time-independent complexity, i.e., real complexity and imaginary complexity. The vector sum is called absolute complexity. Real complexity of coupled design is larger than that of uncoupled or decoupled designs. Imaginary complexity can be reduced when the design matrix is known. As an example of time-independent imaginary complexity, the design of a printing machine based on xerography is discussed. There are two kinds of time-dependent real complexity: time-dependent combinatorial complexity and time-dependent periodic complexity. Using a robot-scheduling problem as an example, it is shown that a coupled design with a combinatorial complexity can be reduced to a decoupled design with periodic complexity. The introduction of periodicity simplifies the design by making it deterministic, which requires much less information. Whenever a combinatorial complexity is converted to a periodic complexity, complexity and uncertainty is reduced and design simplified.     

A multi-agent system for chemical supply chain simulation and management support

Modern chemical production is customer-driven and the desired delivery time for the products is often shorter than their campaign length. In addition, the raw materials supplying time is often long. These features make it desirable to provide tools to support collaborative supply chain decision making, preferably over the Internet, and where there are conflicts, compromise decisions can be quickly reached and the effects of the decisions can be quantitatively simulated. This paper des cribes such a multi-agent system (MAS) that can be used to simulate the dynamic behaviour and support the management of chemical supply chains over the Internet. Geographically distributed retailers, logistics, warehouses, plants and raw material suppliers are modelled as an open and re-configurable network of co-operative agents, each performing one or more supply chain functions. Communication between agents is made through the common agent communication language KQML (knowledge query message language). A t the simulation layer, the MAS allows distributed simulation of the chain behaviour dynamically, so that compromise decisions can be rapidly and quantitatively evaluated. Because in a chemical supply chain the scheduling of the plant often dominates the chain performance, an optimum scheduling system for batch plants is integrated into the MAS. The functions of the system are illustrated by reference to a case study for the supply and manufacture using a multi-purpose batch plant of paints and coatings.     

A Mathematical Framework for the Key Characteristic Process

To maximize product quality, a product design team selects concepts and dimensions to minimize a product’s sensitivity to variation. However, even for the most robust products, it is rarely possible to transition a product into production without encountering any variation-related problems. In a complex product, it is not economically or logistically feasible to control and/or monitor the thousands of tolerances specified in a product’s drawing set. To address this problem, many organizations are using Key Characteristic (KCs) methods to identify where excess variation will most significantly affect product quality, and what product features and tolerances require special attention from manufacturing. As simple as this principle seems, most companies struggle to effectively implement KC methods because no quantitative methods to prioritize KCs exist. This paper develops a mathematical definition of a KC based on a variation propagation model. In addition, it develops a quantitative effectiveness measure used to prioritize where verification, variation reduction, and on-going monitoring should be applied. The effectiveness measure incorporates the cost of control, the benefit of control, and the expected change in process capability. The methods are illustrated using an automotive door assembly.     

Decision support for AIDS control programmes in Eastern Africa

The Acquired Immune Deficiency Syndrome (AIDS) constitutes the worst hazard to health care systems in Eastern Africa. Misallocation of scarce resources of AIDS Control Programmes will unavoidably lead to additional infections and casualties. The following paper discusses a system dynamics model which allows to assess the impact of different interventions on a pattern population in Eastern Africa. It becomes obvious that short- and long-term consequences of these programmes differ significantly. The optimal allocation of resources, therefore, is highly complex and calls for decision support systems to sustain AIDS control programmes.     

A bottleneck assignment approach to the multiple container loading problem

The container loading problem addresses the question of how to store several three dimensional, rectangular items (e.g. boxes) in one or more containers in such a way that maximum use is made of the container space. The multiple container problem concentrates on the situation where the consignment to be loaded cannot be accommodated in a single container. To minimize the number of required containers the repeated application of a single container approach is often suggested in the literature. In contrast, in this paper an approach based on a set partitioning formulation of the problem is presented. Within this approach a single container algorithm is used to produce alternative loading patterns. This approach easily allows introducing additional aspects, e.g. separation of boxes or complete shipment of boxes.     

Internet-Based Design Catalogue for the Shaft and Bearing

The Internet and World Wide Web (WWW) are evolving as an important communication technology. This paper examines the development of an Internet-based online catalogue on the WWW. An interactive website is prepared that helps a remote designer to design shafts and bearings based on various input parameters provided. The web site also provides solid models of the shaft to perform CAD and FEM analysis. This permits the user to make further investigations, and helps to modify the design satisfactory.     

Evaluation Metrics for the Rating and Optimization of Snap-fits

Current snap-fit design guides recommend sizing snap-fit features on the basis of insertion force and allowable strain during assembly. Retention force information in such guides is often inaccurate, although this is considered to be the primary attribute of the snap-fit after assembly. The authors contend that these (insertion force, allowable strain, retention force) are not the only critical performance criteria for snap-fit features. Designers have to contend with several other constraints and design requirements. Additional performance metrics for snap-fit features are proposed by drawing upon considerable experience with plastic part design issues. Locking ratio, dimensional and volumetric retention force, consideration of the characteristic dimension of the joint and snap-fit, feature stiffness, required over-insertion and consideration of snap-fit strength relative to part strength are proposed to supplement currently used metrics for evaluating and rating snap-fit designs. The applicability of these metrics is illustrated with real-life examples, and their merits and demerits discussed. A chart of achievable locking ratios for different snap-fit topologies is presented for use as a design tool for the initial selection of snap-fit topologies. Its use as a rational basis for selection and optimization of snap-fits is suggested. Adoption of proposed metrics will allow designers to better quantify, and thereby optimize the performance of, snap-fit features. These ideas will be built upon in the future, and used as a basis for a comprehensive snap-fit selection and detailed design tool.     

A Dominance-based Design Metric in Multiattribute Robust Design

This paper outlines the development of an effective and consistent ‘designing-in-quality’ strategy that can be used to deal with concepts of uncertainty, quality and robustness in engineering design. Specifically, this paper presents a decision analysis-based robust design metric that seamlessly integrates objective evaluations on the goodness of a design alternative with the designer’s intent and preferences. This is achieved through the development of a set of performance-reflecting dominance indices for the attributes and their utilization in a preference-influenced multiattribute utility formulation. Such a knowledge feedback-based decision model development will be particularly useful when dealing with complex iteration-based engineering design process where little information on the expected outcomes may be known a priori, or where product performance is computationally expensive to evaluate. Application of this robust design metric in a multi-stage experimentation and modeling design process is presented. The characteristics of the proposed design metric and the effectiveness of the overall design procedure in dealing with constrained engineering design problems are examined with the aid of demonstrative case studies and the results are discussed.