Thesis (Ph.D.)--Lehigh University, 2009. / Advisers: Jeff T. Linderoth; Robert H. Storer.

Thesis (M.B.A.)--University of Hong Kong, 1985.

Thesis--PlanB (M.S.)--University of Wisconsin--Stout, 2002. / Includes bibliographical references.

Thesis--PlanB (M.S.)--University of Wisconsin--Stout, 2002. / Includes bibliographical references.

The purpose of this study was to construct and field-test a standardized instrument for assessing the attitudes of employees toward a Quality of Working Life (QWL) program. The QWL movement is one response to the increasing demand for organizational change efforts, an intervention which elects worker representatives to jointly-established union-management committee structures, thereby democratizing the workplace. The instrument finalized was the Quality of Working Life Attitude Scale (QWLAS), a 29-item Likert-format inventory developed through the administration of an 8^-item Pilot Form within the Department of Transportation of Pima County, Arizona. The following research questions were addressed: (1) What basic factors comprise the concept of QWL attitude as measured by the QWLAS?; (2) What items can comprise the final QWLAS Long Form and Short Form without significantly lowering scale reliability?; (3) Is the QWLAS a reliable psychological instrument?; and (k) Is the QWLAS a valid psychological instrument? A total of 179 respondents returned the completed Pilot Form, and data analysis was performed utilizing the Statistical Package for the Social Sciences. Confirmatory factor analysis employing a principal factors analysis with a varimax rotation, as well as coefficient alpha tests of internal consistency and subscale intercorrelations, revealed that the rationally-derived initial subscales did not possess sufficient factoral validity, homogeneity, or statistical independence to warrant their being kept intact in the final QWLAS forms. Exploratory factor analysis surfaced two interpretable factors, the first being labeled General and consisting of 17 positively-worded items concerning more global feelings and ideas about the theory of the program. The second factor, Specific Concerns, consisted of 12 negatively-worded items about more practical realities of QWL. A 29-item QWLAS Long Form and 14-item QWLAS Short Form were finalized around these two components. Cronbach's alpha estimate of reliability yielded high coefficients of .96, .95 and .93 for the Pilot Form, Long Form, and Short Form, respectively. All forms were reviewed favorably against face, content, concurrent and construct validity. The QWLAS results suggest it reliably and validly discriminates favorable versus unfavorable QWL attitudes. Recommendations include further factor validation and use of the QWLAS to research attitudes toward QWL.

This dissertation presents a statistical model and analysis procedure for product performance aging degradation data. This model takes into account the strictly increasing/decreasing nature of performance measurements at multiple observation times. Maximum likelihood estimation (MLE) is used to estimate the time varying parameters of the proposed statistical model. The analysis of both generated data and field data is presented. To demonstrate product reliability under aging, an analysis of surface mounted solder joints due to thermal fatigue is included in the dissertation. This analysis was done by first examining published life test data and then identifying the intermetallic compound (IMC) thickness randomness. Results indicate that the IMC layer thickness randomness may have significant influence on the Mean Time To Failure (MTTF) and the reliability at high thermal cycles. The analysis of products with competing hard and soft failure modes is presented in terms of distribution independence. Derivation and examples are included for the event when the product finally fails in a specific failure mode. Finally, an improved strength-stress interference (SSI) reliability model is derived for analyzing a more general engineering degradation problem. This model incorporates both stochastic strength aging degradation and the stochastic loading force directed at the product. Statistical inference for simple stochastic processes and numerical examples are analyzed and discussed to verify the model.

The House of Quality (HOQ) has been widely discussed as a mechanism for capturing the Voice of the Customer and guiding the process of converting the customer's voice into internal engineering specifications. However, the discussion of this process to date has tended to be qualitative rather than quantitative. Various heuristic practices have evolved with little substantiation of their value or evaluation of their impact other than illustration in a few case studies. Examples of practices promoted by several authors and practitioners include the inclusion of the relative magnitude of effects, but not direction, in the body of the matrix; the restriction of relationships to an integer scale of subjective, ratio values; and allocating available engineering resources to the hard-to-improve characteristics (because the easy ones will presumably take care of themselves). The process for setting target specifications given the HOQ data has not been well defined either. Design teams are required to develop their own ad hoc rules. When multiple engineering characteristics affect a single customer attribute or when an engineering characteristic impacts multiple customer attributes, the design problem becomes difficult and current procedures are of little use to the design team. This is particularly true when some interactions are negative. The result may be lost opportunity from the selection of non-optimal designs. This research takes a scientific approach to optimally specifying the target values for engineering characteristics in a competitive marketplace. A methodology for building linear or nonlinear statistical models of customer preference (value) for each customer attribute followed by an optimization routine that will obtain the optimal specification of engineering characteristics is proposed. The optimization model considers economic and technological constraints as well as customer preferences. The process results in optimal, feasible design specifications. In addition the effect of variability in parameter estimates on the ability to correctly identify the key engineering characteristics for optimizing customer value is investigated. Model performance is also analyzed through random generation of 320 problem instances of varying linearity, size, density, monotonicity and correlation. Finally, the methodology is applied to a problem from industry and the results are compared with an actual, subjectively-derived design.

The Conditional Covering Problem (CCP) is a facility location problem on a graph, where the set of nodes represents the demand points and the potential facility locations. The CCP minimizes the sum of the facility location costs required to cover all demand points. The key aspect of the CCP is that a facility covers all nodes within a given coverage radius, except for the node on which it is located. Our investigation of the CCP will first show that solving CCP on a general graph structure is NP-Hard, prohibiting finding exact optimal solutions in a finite amount of time. While the CCP is NP-Hard on general graphs, we will present a quadratic algorithm that will find optimal solutions to CCP on path and extended star graphs (multiple path graphs with one node in common). We will then present a polynomial time algorithm for tree graphs building off the quadratic algorithms for a star and tree. Given that CCP is NP-Hard on general graphs we next focused on determining near optimal solutions for general graphs. We applied both greedy heuristics and metaheuristics to determine near-optimal solutions. Building off our understanding of optimal solutions on tree structures, we incorporate the idea of trees into our heuristic search. We found that greedy heuristics provide near-optimal solutions in a very short period of time. We showed that simulated annealing with binary encoding provided higher quality solutions to the CCP.

This dissertation examines scheduling in flexible flow lines with sequence-dependent setup times to minimize makespan. This type of manufacturing environment is found in industries such as printed circuit board and automobile manufacture. Lower makespans can be associated with more efficient use of resources. Poor scheduling when sequence-dependent setup times exist can negatively impact productivity. As a building block, minimizing makespan in parallel identical machines with sequence-dependent setup times is examined. Several heuristics are compared empirically using statistical analysis. Experimental results indicate that a heuristic based on the Insertion Heuristic for the Travelling Salesman Problem is effective. Subsequently, minimizing makespan in flexible flow lines with sequence-dependent setup times is considered. An integer program that incorporates all aspects of the problem is formulated. Due to the NP-hard nature of the problem, heuristic methods are considered. The heuristics, based on greedy methods, flow line methods, the Insertion Heuristic for the Travelling Salesman Problem and genetic algorithms are compared empirically using statistical analysis. The heuristics are designed to take advantage of the flow line nature of the problem, the parallel machine nature and the combinatorial features of the problem. Problem data is generated in order to evaluate the heuristics. The characteristics are chosen to reflect those used by previous researchers. An effective lower bound is created in order to evaluate the heuristics. A random keys genetic algorithm is found to be very effective for the problems eyed. In addition, several extensions based on backwards pass of the schedule and focusing on the bottleneck stage are proposed and examined. These proved to be ineffective approaches but yielded insight regarding what features of schedule are important. Most significantly, the first stage is very important in determining the quality of the subsequent schedule. The heuristics considered here focus on setting a schedule for one stage and then considering the next. Areas for future research include developing methods of scheduling job-by-job and examination of branch and bound methods to find optimal solutions, aided by effective lower bounds and theorems regarding schedule domination.

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