Thomas J. Crowe

An integrated dynamic performance measurement system for improving manufacturing competitiveness

Abstract Until the 1980s manufacturing companies relied solely on performance measurement systems based on traditional cost accounting systems to control, monitor, and improve their operations. However, it has been shown that these systems do not capture the relevant performance issues for todays manufacturing environment. Rather, they focus on monitoring and controlling versus supporting process improvement, promoting overall system optimization, and addressing the dynamics of changing systems. In order to overcome the limitations of the traditional performance measurement systems a variety of integrated systems have been proposed. However, these systems have not yet fully addressed the requirements of a performance measurement system for todays manufacturing environment. This paper presents an integrated dynamic performance measurement system (IDPMS) developed in conjunction with the Missouri Plant of Square D Company. The IDPMS integrates three main areas of the company: management, process improvement team, and factory shop floor. To achieve an integrated system, the three areas are linked through the specification, reporting and dynamic updating of the defined areas of success, performance measures, and performance standards. Three tools are incorporated to support and enhance the integration within the IDPMS. An example is given that illustrates how the IDPMS addresses the current requirements of a performance measurement system.

Using quality function deployment in manufacturing strategic planning

Describes efforts to extend the use of quality function deployment (QFD) to manufacturing strategy development. QFD uses a house of quality to translate the “voice of the customer” into engineering specifications. Originally developed and applied as a powerful tool for concurrent product and process design, QFD is widely used in industry as a technique within total quality management (TQM). The approach has only recently been applied in strategic planning. Describes how the traditional QFD concepts and methods can be used in the formulation of manufacturing strategy to ensure alignment with business strategy. Presents a case study at a powdered metals manufacturer to show how the QFD methodology can be adapted for use in manufacturing strategy formulation.

Multi‐attribute analysis of ISO 9000 registration using AHP

Quality improvement continues to be an important international business strategy as we enter the twenty‐first century. Legal requirements, customer demand, market pressure, competition, and the need for in‐house quality improvement has driven more companies to become ISO 9000 registered. Implementing ISO 9000 is expensive, time‐consuming, and requires significant dedication and effort. Investment in such a project calls for detailed analysis and justification. This research paper proposes a multi‐attribute analysis and justification model based on the analytical hierarchy process (AHP) for implementing the ISO 9000 quality system standard. The model is developed based on case studies at companies which underwent the process of registration and by the synthesis of relevant literature both on ISO 9000 and techniques of analysing similar projects. The model has been applied and validated in companies that are both ISO 9000 registered and are pursuing ISO 9000.

Quantitative risk level estimation of business process reengineering efforts

With risk defined as the possibility of deviation in the results from the expected goals, business process reengineering (BPR) initiatives clearly involve risk taking. However, due to the high expected returns of such efforts, the acceptable risk levels of BPR will tend to be greater than those of less ambitious projects. This research reports the development of a tool to quantitatively estimate the potential risk level of a BPR effort before an organization commits its resources to that effort. The underlying research employed a survey of BPR‐experienced organizations to collect assessment information in order to build a BPR risk estimation model. The developed tool uses triangular fuzzy numbers to approximate the degree of success/failure of proposed BPR initiatives. The tool can be applied by any organization contemplating BPR, thus giving such organizations a heretofore unavailable estimate of the risk level of proposed BPR efforts. Validation was performed based upon an 18‐month BPR project conducted at the Missouri Lottery.

A proposed structure for distributed shopfloor control

Discusses the movement away from hierarchical organizational structures towards flatter, heterarchical, structures which is reflected in the growing interest in distributed manufacturing control systems. Traditional hierarchical control systems are limited by the breadth, quantity and timeliness of information needed for their operation. Distributed, heterarchical, control systems overcome these hierarchical limitations but, concurrently, forfeit advantages of the hierarchy including analytically optimal loading patterns and centralized pristine data tracking. Classifies existing research into four categories and documents a progression of heterarchical control approaches to inject some of the advantages of the traditional hierarchy into new heterarchical frameworks. Concludes that neither hierarchical nor heterarchical control structures are ideal in their pure form and, hence, proposes a modified structure, called the quasi‐heterarchical control system, which is a combination of, and a compromise betwee...

Deciding manufacturing priorities: Flexibility, cost, quality and service

Abstract Traditional manufacturing planning focuses first on understanding the realities of the product marketplace and then aligning the production processes to match those realities. By conforming to that independent-market dependent-production model and simply implementing the determined tactics, manufacturing misses the opportunity to create competitive advantage by adopting a strategy that enhances the firms position. To illustrate how manufacturing can incorporate strategic objectives into its planning, we add a third dimension to the traditional two-dimensional form of the product—process matrix. Along the new axis we show how four key competitive thrusts relate to the stages of the product—process life cycles. The thrusts of flexibility, cost, quality, and service are made explicit by plotting them, in turn, against the stages in the evolution of the product and the process. Each plot reveals new ways for manufacturing to plan for and realize competitive advantage through the application of computer-integrated manufacturing principles.

An example of the application of production system design tools for the implementation of business process reengineering

Abstract The concepts behind business process reengineering (BPR) have become an important management tool and are likely here to stay. There have been a variety of BPR implementation approaches developed, but many of them lack the specifies required for an actual BPR implementation. This paper illustrates how borrowing from the approaches developed for production system design, specifically, binary ordering for machine cell formation for forming business process teams, can open up a whole area of existing tools that can assist in BPR implementation. Simple, yet powerful, the resulting methodology can increase the efficacy of BPR efforts.

Selecting business process reengineering projects strategically

Business processes are defined as sequences of linked functional-level activities which take inputs and produce outputs. And Business Process Reengineering (BPR) is defined as the analysis and radical redesign of the business processes within a firm. Undertaking BPR is a high-risk, high-reward proposition. The payback for doing BPR correctly is enormous: 200% to 1000% improvements in key business performance measures are documented. But with those potential rewards comes high risks: studies show more than two-thirds of BPR attempts fail. The research reported in this paper develops a BPR decision support system to reduce the risks while maintaining or improving the rewards. The system is being applied at five U.S. electronics companies where preliminary results look very promising.

Selecting BPR projects based on strategic objectives

An extensive search has shown that no business process reengineering (BPR) method specifically addresses the issue of selecting business processes for reengineering based on the processes’ impact on the firm’s strategic objectives. Focusing on strategic business units (SBUs) within the electronics and electrical components industry, the research reported in this paper develops a generic set of SBU business processes which is used, in conjunction with an existing set of generic strategic objectives, to create a decision model that assesses the performance and improvement potential of each business process with respect to the SBU’s collective strategic objectives. The decision model, which contains both deterministic and stochastic elements, is based upon the concepts of decision tree analysis and influence diagramming. Validation of both the set of business processes and the decision support system has been conducted through field studies at electronics and electrical components companies. The results from these studies have been very promising.

A fuzzy parametrical forward- and backward-chained two-dimensional attribute decision model

To operate strategically, corporate decision-makers need to assess functional-level projects based upon their ability to fulfill higher-level strategic business objectives. To support such decision-making, a model framework is developed that first aggregates expected project performance across individual business activities using an additive value function and, second, across the strategic objectives of the business using a displaced ideal approach. The two-dimensional (2-D) model can be applied iteratively in a define-analyze-refine cycle that highlights how proposed functional-level projects can be enhanced to better fulfill business-level strategic objectives. To deal with the imprecision introduced due to the strategic infrequent decision situations in which the model is used, the user inputs are defined as, and the model is developed using, fuzzy numbers. Operationalized as a computer-based decision support system, the model has been successfully applied at four electronics manufacturers.