Analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

The order selection and lot sizing problem in the make-to-order environment

This research is motivated by the need for considering lot sizing while accepting customer orders in a make-to-order (MTO) environment, in which each customer order must be delivered by its due date. Job shop is the typical operation model used in an MTO operation, where the production planner must make three concurrent decisions; they are order selection, lot size, and job schedule. These decisions are usually treated separately in the literature and are mostly led to heuristic solutions. The first phase of the study is focused on a formal definition of the problem. Mathematical programming techniques are applied to modeling this problem in terms of its objective, decision variables, and constraints. A commercial solver, CPLEX is applied to solve the resulting mixed-integer linear programming model with small instances to validate the mathematical formulation. The computational result shows it is not practical for solving problems of industrial size, using a commercial solver. The second phase of this study is focused on development of an effective solution approach to this problem of large scale. The proposed solution approach is an iterative process involving three sequential decision steps of order selection, lot sizing, and lot scheduling. A range of simple sequencing rules are identified for each of the three subproblems. Using computer simulation as the tool, an experiment is designed to evaluate their performance against a set of system parameters. For order selection, the proposed weighted most profit rule performs the best. The shifting bottleneck and the earliest operation finish time both are the best scheduling rules. For lot sizing, the proposed minimum cost increase heuristic, based on the Dixon-Silver method performs the best, when the demand-to-capacity ratio at the bottleneck machine is high. The proposed minimum cost heuristic, based on the Wagner-Whitin algorithm is the best lot-sizing heuristic for shops of a low demand-to-capacity ratio. The proposed heuristic is applied to an industrial case to further evaluate its performance. The result shows it can improve an average of total profit by 16.62%. This research contributes to the production planning research community with a complete mathematical definition of the problem and an effective solution approach to solving the problem of industry scale.

Branch and price solution approach for order acceptance and capacity planning in make -to -order operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

An examination of psychological meaningfulness, safety, and availability as the underlying mechanisms linking job features and personal characteristics to work engagement

The present study tested a nomological net of work engagement that was derived from its extant research. Two of the main work engagement models that have been presented and empirically tested in the literature, the JD-R model and Kahn's model, were integrated to test the effects that job features and personal characteristics can have on work engagement through the psychological conditions of meaningfulness, safety, and availability. In this study, safety refers to psychological perceptions of safety and not workplace safety behaviors. The job features that were tested in this model included person-job fit, autonomy, co-worker relations, supervisor support, procedural justice, and interactional justice, while the personal characteristics consisted of self-consciousness, self-efficacy, extraversion, and neuroticism. Thirty-four hypotheses and a conceptual model were tested in order to establish the viability of this nomological net of work engagement in which it was expected that meaningfulness would mediate the relationships between job features and work engagement, safety would mediate the relationships that job features and personal characteristics have with work engagement, and availability (physical, emotional, and cognitive resources) would mediate the relationships that personal characteristics have with work engagement. Furthermore, analyses were run in order to determine the factor structure of work engagement, assess whether or not it exhibits differential validity from organizational commitment and job satisfaction, and confirm that it is positively related to the outcome variable of organizational citizenship behavior (OCB). The final sample consisted of 500 workers from an online labor market who responded to a questionnaire composed of measures of all constructs included in this study. Findings show that work engagement is best represented as a three-factor construct, composed of vigor, dedication and absorption. Furthermore, support was found for the distinction of work engagement from the related constructs of organizational commitment and job satisfaction. With regard to the proposed model, meaningfulness proved to be the strongest predictor of work engagement. Results show that it partially mediates the relationships that all job features have with work engagement. Safety proved to be a partial mediator of the relationships that autonomy, co-worker relations, supervisor support, procedural justice, interactional justice, and self-efficacy have with work engagement, and fully mediate the relationship between neuroticism and work engagement. Findings also show that availability partially mediates the positive relationships that extraversion and self-efficacy have with work engagement, and fully mediates the negative relationship that neuroticism has with work engagement. Finally, a positive relationship was found between work engagement and OCB. Research and organizational implications are discussed.

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

The Validity of Broad and Narrow Personality Traits For Predicting Job Performance: The Differential Effects of Time

Research into the dynamicity of job performance criteria has found evidence suggesting the presence of rank-order changes to job performance scores across time as well as intraindividual trajectories in job performance scores across time. These findings have influenced a large body of research into (a) the dynamicity of validities of individual differences predictors of job performance and (b) the relationship between individual differences predictors of job performance and intraindividual trajectories of job performance. In the present dissertation, I addressed these issues within the context of the Five Factor Model of personality. The Five Factor Model is arranged hierarchically, with five broad higher-order factors subsuming a number of more narrowly tailored personality facets. Research has debated the relative merits of broad versus narrow traits for predicting job performance, but the entire body of research has addressed the issue from a static perspective -- by examining the relative magnitude of validities of global factors versus their facets. While research along these lines has been enlightening, theoretical perspectives suggest that the validities of global factors versus their facets may differ in their stability across time. Thus, research is needed to not only compare the relative magnitude of validities of global factors versus their facets at a single point in time, but also to compare the relative stability of validities of global factors versus their facets across time. Also necessary to advance cumulative knowledge concerning intraindividual performance trajectories is research into broad vs. narrow traits for predicting such trajectories. In the present dissertation, I addressed these issues using a four-year longitudinal design. The results indicated that the validities of global conscientiousness were stable across time, while the validities of conscientiousness facets were more likely to fluctuate. However, the validities of emotional stability and extraversion facets were no more likely to fluctuate across time than those of the factors. Finally, while some personality factors and facets predicted performance intercepts (i.e., performance at the first measurement occasion), my results failed to indicate a significant effect of any personality variable on performance growth. Implications for research and practice are discussed.

An Examination of Psychological Meaningfulness, Safety, and Availability as the Underlying Mechanisms linking Job Features and Personal Characteristics to Work Engagement

The present study tested a nomological net of work engagement that was derived from its extant research. Two of the main work engagement models that have been presented and empirically tested in the literature, the JD-R model and Kahn’s model, were integrated to test the effects that job features and personal characteristics can have on work engagement through the psychological conditions of meaningfulness, safety, and availability. In this study, safety refers to psychological perceptions of safety and not workplace safety behaviors. The job features that were tested in this model included person-job fit, autonomy, co-worker relations, supervisor support, procedural justice, and interactional justice, while the personal characteristics consisted of self-consciousness, self-efficacy, extraversion, and neuroticism. Thirty-four hypotheses and a conceptual model were tested in order to establish the viability of this nomological net of work engagement in which it was expected that meaningfulness would mediate the relationships between job features and work engagement, safety would mediate the relationships that job features and personal characteristics have with work engagement, and availability (physical, emotional, and cognitive resources) would mediate the relationships that personal characteristics have with work engagement. Furthermore, analyses were run in order to determine the factor structure of work engagement, assess whether or not it exhibits differential validity from organizational commitment and job satisfaction, and confirm that it is positively related to the outcome variable of organizational citizenship behavior (OCB). The final sample consisted of 500 workers from an online labor market who responded to a questionnaire composed of measures of all constructs included in this study. Findings show that work engagement is best represented as a three-factor construct, composed of vigor, dedication and absorption. Furthermore, support was found for the distinction of work engagement from the related constructs of organizational commitment and job satisfaction. With regard to the proposed model, meaningfulness proved to be the strongest predictor of work engagement. Results show that it partially mediates the relationships that all job features have with work engagement. Safety proved to be a partial mediator of the relationships that autonomy, co-worker relations, supervisor support, procedural justice, interactional justice, and self-efficacy have with work engagement, and fully mediate the relationship between neuroticism and work engagement. Findings also show that availability partially mediates the positive relationships that extraversion and self-efficacy have with work engagement, and fully mediates the negative relationship that neuroticism has with work engagement. Finally, a positive relationship was found between work engagement and OCB. Research and organizational implications are discussed.