The choice of an efficient and effective production control mechanism (PCM)along with the appropriate buffer allocation pattern is very important for anyproduction engineer/decision maker when designing a production line in order toattain the required system performance. This project work aims to give an insightwith different PCMs, different buffer allocation patterns and arrangement ofworkers of different capability to help the production engineers/decision makersto select the right mechanism and pattern. This study has been performed withmulti-objective simulation optimisation (MOSO) tool. The result from manyexperiments have shown that the ascending buffer allocation pattern stands outas the prominent choice when the goal was to attain maximum throughput (TP)and simultaneously keeping minimum cycle time (CT) and work in process (WIP).The PCMs and workers imbalance patterns performance is different in differentregions of the Pareto-optimal CT-TP data plots obtained from MOSO so theirselection is depending on the interest of the desired level of throughput togetherwith the limit of cycle time.

The focuses of this dissertation are problems of batch production scheduling problems for perishable products with setup times, with the main applications in answering production planning problems faced by manufacturers of perishable products, such as beers, vaccines and yoghurts. The benefits of effective production plans can help companies reduce their total costs substantially to gain the competitive advantages without reduction of the service level in a globalize economy. We develop concepts and methodologies that are applied in two fundamental problems: (i) the batch production scheduling problem for perishable products with sequence-independent setup times (BPP-SI) and (ii) the batch production scheduling problem for perishable products with sequence-dependent setup times (BPP-SD). The problem is that given a set of forecast demand for perishables products to be produced by a set of parallel machines in the single stage of batch production, with each product having fixed shelf-life times and each machine requiring setup times before producing a batch of product, find the master production schedule which minimizes total cost over a specified time horizon. We present the new models for both problems by formulating them as a Mixed Integer Program (MIP) on the discrete time. Computational studies in BPP-SI and BPP-SD for industrial problems are presented. In order to efficiently solve the large BPP-SI problems in practice, we develop the five efficient heuristics. The extensive computational results show that the developed heuristics can obtain the good solution for the very large problem size and require very short amount of computational time.

<p>The choice of an efficient and effective production control mechanism (PCM)along with the appropriate buffer allocation pattern is very important for anyproduction engineer/decision maker when designing a production line in order toattain the required system performance. This project work aims to give an insightwith different PCMs, different buffer allocation patterns and arrangement ofworkers of different capability to help the production engineers/decision makersto select the right mechanism and pattern. This study has been performed withmulti-objective simulation optimisation (MOSO) tool. The result from manyexperiments have shown that the ascending buffer allocation pattern stands outas the prominent choice when the goal was to attain maximum throughput (TP)and simultaneously keeping minimum cycle time (CT) and work in process (WIP).The PCMs and workers imbalance patterns performance is different in differentregions of the Pareto-optimal CT-TP data plots obtained from MOSO so theirselection is depending on the interest of the desired level of throughput togetherwith the limit of cycle time.</p>

Semiconductor manufacturing is characterized by a dynamic, varying environment and the technology to produce integrated circuits is always shifting in response to the demand for faster and new products, and the time between the development of a new profitable method of manufacturing and its transfer to tangible production is very short. The semiconductor industry has adopted the use of advanced process control (APC), namely a set of automated methodologies to reach desired process goals in operating individual process steps. That is because the ultimate motivation for APC is improved device yield and a typical semiconductor manufacturing process can have several hundred unit processes, any of which could be a yield limiter if a given unit procedure is out of control. APC uses information about the materials to be processed, metrology data, and the desired output results to choose which model and control plan to employ. The current focus of APC for semiconductor manufacturers is run-to-run control. Many metrology applications have become key enablers for the conventionally labeled “value-added” processing steps in lithography and etch and are now integral parts of these processes. The economic advantage of effective metrology applications increases with the difficulty of the manufacturing process. Frequent measurement facilitates products reaching its target but it increases the cost and cycle time. If lots of measurements are skipped, the product quality does not be guaranteed due to process error from uncompensated drift and step disturbance. Thus, it is necessary to optimize the sampling plan in order to quickly identify the sources of prediction errors and decrease the metrology cost and cycle time. The goal of this research intend to understand the relationship between metrology and advanced process control (APC) in semiconductor manufacturing and develop an enhanced sampling strategy in order to maximize the value of metrology and control for critical wafer features. / text

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The integration of production and distribution decisions presents a challenging problem for manufacturers trying to optimize their supply chain. At the planning level, the immediate goal is to coordinate production, inventory, and delivery to meet customer demand so that the corresponding costs are minimized. Achieving this goal provides the foundations for streamlining the logistics network and for integrating other operational and financial components of the system. In this paper, a model is presented that includes a single production facility, a set of customers with time varying demand, a finite planning horizon, and a fleet of vehicles for making the deliveries. Demand can be satisfied from either inventory held at the customer sites or from daily product distribution. A procedure centering on a reactive tabu search is developed for solving the full problem. After a solution is found, path relinking is applied to improve the results. A novel feature of the methodology is the use of an allocation model in the form of a mixed integer program to find good feasible solutions that serve as starting points for the tabu search. Lower bounds on the optimum are obtained by solving a modified version of the allocation model. Computational testing on a set of 90 benchmark instances with up to 200 customers and 20 time periods demonstrates the effectiveness of the approach. In all cases, improvements ranging from 10 - 20% were realized when compared to those obtained from an existing greedy randomized adaptive search procedure (GRASP). This often came at a three- to five-fold increase in runtime, however. A hybrid scheme that combines the features of reactive tabu search algorithm and branch-and-price algorithm is also developed. The combined approach takes advantage of the efficiency of the tabu search heuristic and the precision of the branch-and-price algorithm. Branching strategy that is suitable for the problem is proposed. Several advance techniques such as column generation heuristic and rounding heuristic are also implemented to improve the efficiency of the algorithm. Computational testing on standard data sets shows that a hybrid algorithm can practically solve instances with up to 50 customers and 8 time periods which is not possible by standard branch-and-price algorithm alone. / text

published_or_final_version / Mathematics / Master / Master of Philosophy

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