Derya A. Jacobs

A methodology for analysis of complex sociotechnical processes

This article presents the design and application of a Modified Sociotechnical Systems (MoSTS) methodology for holistic analysis of complex technical processes. Successes and failures of process redesign initiatives have demonstrated the strong influence of human elements on outcomes. (Sociotechnical Systems) STS provides a foundation for structured analysis and redesign of complex processes which emphasizes human aspects in process redesign. The MoSTS methodology is developed from STS research and practice and applied to analyze a complex technical process in the research and development sector. MoSTS is shown to be an effective methodology to facilitate analysis for process redesign, particularly where human influences may have a significant impact on success. The article concludes with limitations and implications for process analysis based on the MoSTS methodology application.

Using Quality Function Deployment as a Framework for Process Measurement

ABSTRACTThis article discusses adopting quality function deployment to develop an effective and efficient process measurement program. The project was conducted at the Naval Undersea Warfare Center (NUWC) in Norfolk, Virginia, over a 5-month period. The objective was to develop a measurement program for a software maintenance by identifying the critical metrics for the entire process. As a result, 23 quality metrics were developed for NUWCs process measurement program. Also discussed are the benefits achieved during the quality function deployment process.

Training artificial neural networks for statistical process control

The use of artificial neural networks (ANNs) in statistical process control (SPC) is studied. An ANN is developed in order to determine the status of a process. The objective of the network is to be able to classify the incoming X-Bar values by indicating the status of the process with the appropriate rule. The network is presented with ten values which can be out of control, as described by any of the selected rules. The resulting output is the representation of that particular rule. Several simulations are performed. The features of ANNs which make them desirable for SPC applications are summarized.<<ETX>>

A market attraction model for predicting the US market share of large civil aircraft

With global annual sales exceeding

Team-Based Methods To Analyze High-Technology Production Systems

65 billion, the large civil aircraft industry is an important economic and strategic element of the European Union and US economies. Here we define large civil aircraft (LCA) as those aircraft with capacities exceeding 121 passengers and dedicated to the air passenger market served by commercial airlines. This paper employs a transformed log-centered market attraction model to forecast the US market share of LCA. This model specification ensures that the predicted market share is in the range [0,1] and that the sum of all predicted market shares is equal to 1.0, both logical process requirements. In this special case, where there are two producers, the market attraction model becomes a logit regression model. Here we specify the logit regression model as an autoregressive distributed lag model in which US market share is predicted by quantitative and qualitative predictor variables, an autoregressive lag operator and a linear trend component.

The application of backpropagation neural networks to predict the results of combat

Abstract Sociotechnical systems (STS) has previously been successfully deployed to redesign technical and social aspects of work systems. This article discusses the application of a team-based approach to a complex manufacturing process—cryomodule production—in a high-technology production facility. Cryomodules are complex and highly critical components that are the heart of a linear accelerator, which supports state-of-the-art physics experiments. The objectives of this study, which involved a participatory team of Old Dominion University researchers and cryomodule production experts, were to: (1) investigate both technical and organizational aspects of the production operation using an STS team-based approach, (2) identify areas of improvement with the potential to increase production effectiveness and reduce future production costs, and (3) provide recommendations to improve production process effectiveness. We report on the team-based STS methodology developed and the results of deploying the methodology to a complex technical process. Implications for theory and practice are discussed.

TQM and CIM Can Work Together

The information age changes how US Army decision makers predict future trends. The Army is responding with innovative technology to help its planners to understand the complexities of its decisions, and their impacts, as the Army embraces a post Cold War world view. Using neural network technologies is one way to attack this social technical challenge. Several neural networks were developed to predict the outcome of combat battles. The networks were trained with combat battles from a historical database.<<ETX>>

Integrating Virtual Collaborative Engineering into a Freshman Curriculum

ABSTRACTMultiple simultaneous change initiatives are, in general, more difficult to successfully implement than are individual change initiatives. Multiple initiatives, at a minimum, compete for scarce attention, time, and resources and often actually have conflicting objectives or employee behavior requirements. However, CIM and TQM complement each other and are best implemented together. Companies that currently lag behind their competitors in quality and CIM can implement both at the same time as a catch-up strategy.

Assessing Community Fire Risk: A Decision Analysis Based Approach

Experience in distributed virtual collaborative engineering is becoming more and more important as the use of advanced communication and information technologies is transforming engineering companies. To prepare students for this new reality and to respond to corporate demand, universities must begin to incorporate ‘virtual collaborative engineering’ concepts and ‘e-engineering’ technologies into their curricula. In this paper, design, implementation and assessment of a multidisciplinary freshman engineering and technology course is discussed. The aim of the course is to provide students with the necessary skills and practices in the latest methodologies and technologies to apply in a virtual collaborative engineering environment.

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A prototype community fire risk assessment study was performed for accreditation under the National Fire Service Accreditation Program, developed by the International Association of Fire Chiefs (IAFC). The fire risk model used for the study quantifies risk as a function of perceived consequence from a fire and probability of fire at a structure. The consequence from a fire is determined through expert judgment using the Analytic Hierarchy Process (AHP). The probability of fire at a structure is derived from empirical evidence. A simple additive weighting scheme is employed to combine the consequence and probability factors into a single valued measure of perceived fire risk potential for a structure. A classification scheme is then used to group structures according to risk level. The results of this study provide a model and risk assessment tool for fire science practitioners. Language: en