Algorithms for scheduling parallel batch processing machines with non-identical job ready times

This research is motivated by a practical application observed at a printed circuit board (PCB) manufacturing facility. After assembly, the PCBs (or jobs) are tested in environmental stress screening (ESS) chambers (or batch processing machines) to detect early failures. Several PCBs can be simultaneously tested as long as the total size of all the PCBs in the batch does not violate the chamber capacity. PCBs from different production lines arrive dynamically to a queue in front of a set of identical ESS chambers, where they are grouped into batches for testing. Each line delivers PCBs that vary in size and require different testing (or processing) times. Once a batch is formed, its processing time is the longest processing time among the PCBs in the batch, and its ready time is given by the PCB arriving last to the batch. ESS chambers are expensive and a bottleneck. Consequently, its makespan has to be minimized. ^ A mixed-integer formulation is proposed for the problem under study and compared to a formulation recently published. The proposed formulation is better in terms of the number of decision variables, linear constraints and run time. A procedure to compute the lower bound is proposed. For sparse problems (i.e. when job ready times are dispersed widely), the lower bounds are close to optimum. ^ The problem under study is NP-hard. Consequently, five heuristics, two metaheuristics (i.e. simulated annealing (SA) and greedy randomized adaptive search procedure (GRASP)), and a decomposition approach (i.e. column generation) are proposed—especially to solve problem instances which require prohibitively long run times when a commercial solver is used. Extensive experimental study was conducted to evaluate the different solution approaches based on the solution quality and run time. ^ The decomposition approach improved the lower bounds (or linear relaxation solution) of the mixed-integer formulation. At least one of the proposed heuristic outperforms the Modified Delay heuristic from the literature. For sparse problems, almost all the heuristics report a solution close to optimum. GRASP outperforms SA at a higher computational cost. The proposed approaches are viable to implement as the run time is very short. ^

A heuristic algorithm to generate test program sequences for moving probe electronic test equipment

The electronics industry, is experiencing two trends one of which is the drive towards miniaturization of electronic products. The in-circuit testing predominantly used for continuity testing of printed circuit boards (PCB) can no longer meet the demands of smaller size circuits. This has lead to the development of moving probe testing equipment. Moving Probe Test opens up the opportunity to test PCBs where the test points are on a small pitch (distance between points). However, since the test uses probes that move sequentially to perform the test, the total test time is much greater than traditional in-circuit test. While significant effort has concentrated on the equipment design and development, little work has examined algorithms for efficient test sequencing. The test sequence has the greatest impact on total test time, which will determine the production cycle time of the product. Minimizing total test time is a NP-hard problem similar to the traveling salesman problem, except with two traveling salesmen that must coordinate their movements. The main goal of this thesis was to develop a heuristic algorithm to minimize the Flying Probe test time and evaluate the algorithm against a "Nearest Neighbor" algorithm. The algorithm was implemented with Visual Basic and MS Access database. The algorithm was evaluated with actual PCB test data taken from Industry. A statistical analysis with 95% C.C. was performed to test the hypothesis that the proposed algorithm finds a sequence which has a total test time less than the total test time found by the "Nearest Neighbor" approach. Findings demonstrated that the proposed heuristic algorithm reduces the total test time of the test and, therefore, production cycle time can be reduced through proper sequencing.

Exposure to endocrine disrupting compounds and reproductive toxicity in women

The overall objective of the research presented in this dissertation was to assess exposure to endocrine disrupting chemicals (EDCs), polychlorinated biphenyls (PCBs), phthalates, and bisphenol A (BPA) in the general population and evaluate their associations with adverse reproductive health effects, including cancers, in women. Given the proven contribution of unopposed estrogens to the risk for endometrial neoplasia or breast cancer, renewed health concerns have aroused about estrogen mimicking EDCs found in food, personal care products or as environmental contaminants. Our meta-analysis showed that exposure to estrogen mimicking PCBs increased summary risk of breast cancer and endometriosis. We further evaluated the relationship between endometriosis and breast cancer, and EDCs using a bioinformatics method. Our bioinformatics approach was able to identify genes with the potential to be involved in interaction with PCB, phthalates and BPA that may be important to the development of breast cancer and endometriosis. Therefore, we hypothesized that exposure to EDCs such as PCBs, phthalates, and BPA, results in adverse reproductive health effects in women. Using subject data and biomarkers available from the Center for Disease Controls National Health and Nutrition Examination Survey database we conducted a cross-sectional study of EDCs in relation to self-reported history of endometriosis, uterine leiomyomas, breast cancer, cervical cancer, ovarian cancer, and uterine cancer. Significantly higher body burdens of PCBs were found in women diagnosed with breast cancer, ovarian cancer, and uterine cancer compared to women without cancer. PCB 138 was significantly associated with breast cancer, cervical cancer, and uterine cancer, while PCBs 74 and 118 were significantly associated with ovarian cancer. The sum of dioxin-like PCBs were significantly associated with ovarian cancer (OR of 2.02, 95% CI: 1.06-3.85) and the sum of non-dioxin-like PCBs were significantly associated with uterine cancer (OR of 1.12, 95%CI: 1.03-1.23). Significantly higher body burdens of PCBs were also found in women diagnosed with endometriosis and uterine leiomyomas. Documenting the exposure to EDCs among the general U.S. population, and identifying agents associated with reproductive toxicity have the potential to fill research gaps and facilitate our understanding of the complex role environmental chemicals play in producing toxicity in reproductive organs.^

Exposure to Endocrine Disrupting Compounds and Reproductive Toxicity in Women

The overall objective of the research presented in this dissertation was to assess exposure to endocrine disrupting chemicals (EDCs), polychlorinated biphenyls (PCBs), phthalates, and bisphenol A (BPA) in the general population and evaluate their associations with adverse reproductive health effects, including cancers, in women. Given the proven contribution of unopposed estrogens to the risk for endometrial neoplasia or breast cancer, renewed health concerns have aroused about estrogen mimicking EDCs found in food, personal care products or as environmental contaminants. Our meta-analysis showed that exposure to estrogen mimicking PCBs increased summary risk of breast cancer and endometriosis. We further evaluated the relationship between endometriosis and breast cancer, and EDCs using a bioinformatics method. Our bioinformatics approach was able to identify genes with the potential to be involved in interaction with PCB, phthalates and BPA that may be important to the development of breast cancer and endometriosis. Therefore, we hypothesized that exposure to EDCs such as PCBs, phthalates, and BPA, results in adverse reproductive health effects in women. Using subject data and biomarkers available from the Center for Disease Controls National Health and Nutrition Examination Survey database we conducted a cross-sectional study of EDCs in relation to self-reported history of endometriosis, uterine leiomyomas, breast cancer, cervical cancer, ovarian cancer, and uterine cancer. Significantly higher body burdens of PCBs were found in women diagnosed with breast cancer, ovarian cancer, and uterine cancer compared to women without cancer. PCB 138 was significantly associated with breast cancer, cervical cancer, and uterine cancer, while PCBs 74 and 118 were significantly associated with ovarian cancer. The sum of dioxin-like PCBs were significantly associated with ovarian cancer (OR of 2.02, 95% CI: 1.06-3.85) and the sum of non-dioxin-like PCBs were significantly associated with uterine cancer (OR of 1.12, 95%CI: 1.03-1.23). Significantly higher body burdens of PCBs were also found in women diagnosed with endometriosis and uterine leiomyomas. Documenting the exposure to EDCs among the general U.S. population, and identifying agents associated with reproductive toxicity have the potential to fill research gaps and facilitate our understanding of the complex role environmental chemicals play in producing toxicity in reproductive organs.