Thesis (Ph. D.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2006. / Dr. Yih-Long Chang, Committee Member ; Dr. Martin Savelsbergh, Committee Member ; Dr. Leon McGinnis, Committee Co-Chair ; Dr. Gunter Sharp, Committee Chair ; Dr. Doug Bodner, Committee Member ; Dr. Joel Sokol, Committee Member.

O ambiente competitivo no qual as empresas estão inseridas é caracterizado por mudanças frequentes na demanda de seus produtos e por uma necessidade em reduzir custos. Para obter sucesso frente à concorrência, se faz necessário alcançar resultados através da melhoria do processo produtivo, oferecendo respostas mais rápidas a variações na demanda e com uma utilização adequada dos recursos produtivos. Neste contexto, a utilização de softwares Advanced Planning and Scheduling com regra personalizada de programação possibilita melhoria no planejamento e programação da empresa no sentido dos objetivos citados. A partir disso, este trabalho propõe uma sistemática de desenvolvimento e implantação de regras de programação personalizadas. Após, é apresentada aplicação de um caso prático no qual foram detalhadas todas as etapas propostas na sistemática, desde o entendimento das necessidades da empresa até a avaliação dos resultados obtidos. / The competitive environment in which firms operate is characterized by frequent changes in product demand and a necessity to reduce costs. To succeed against the competition, it is necessary to gain competitive advantage by improving the production process, providing faster responses to changes in demand and proper use of productive resources. In this context, the use of Advanced Planning and Scheduling software with custom programming rule allows improved planning and programming company towards the objectives mentioned. This study proposes a systematic development and deployment of custom programming rules, next it is presented a case study which detail the stages proposed in the systematic, from the understanding of the business requirement until the evaluation of results.

O ambiente competitivo no qual as empresas estão inseridas é caracterizado por mudanças frequentes na demanda de seus produtos e por uma necessidade em reduzir custos. Para obter sucesso frente à concorrência, se faz necessário alcançar resultados através da melhoria do processo produtivo, oferecendo respostas mais rápidas a variações na demanda e com uma utilização adequada dos recursos produtivos. Neste contexto, a utilização de softwares Advanced Planning and Scheduling com regra personalizada de programação possibilita melhoria no planejamento e programação da empresa no sentido dos objetivos citados. A partir disso, este trabalho propõe uma sistemática de desenvolvimento e implantação de regras de programação personalizadas. Após, é apresentada aplicação de um caso prático no qual foram detalhadas todas as etapas propostas na sistemática, desde o entendimento das necessidades da empresa até a avaliação dos resultados obtidos. / The competitive environment in which firms operate is characterized by frequent changes in product demand and a necessity to reduce costs. To succeed against the competition, it is necessary to gain competitive advantage by improving the production process, providing faster responses to changes in demand and proper use of productive resources. In this context, the use of Advanced Planning and Scheduling software with custom programming rule allows improved planning and programming company towards the objectives mentioned. This study proposes a systematic development and deployment of custom programming rules, next it is presented a case study which detail the stages proposed in the systematic, from the understanding of the business requirement until the evaluation of results.

O ambiente competitivo no qual as empresas estão inseridas é caracterizado por mudanças frequentes na demanda de seus produtos e por uma necessidade em reduzir custos. Para obter sucesso frente à concorrência, se faz necessário alcançar resultados através da melhoria do processo produtivo, oferecendo respostas mais rápidas a variações na demanda e com uma utilização adequada dos recursos produtivos. Neste contexto, a utilização de softwares Advanced Planning and Scheduling com regra personalizada de programação possibilita melhoria no planejamento e programação da empresa no sentido dos objetivos citados. A partir disso, este trabalho propõe uma sistemática de desenvolvimento e implantação de regras de programação personalizadas. Após, é apresentada aplicação de um caso prático no qual foram detalhadas todas as etapas propostas na sistemática, desde o entendimento das necessidades da empresa até a avaliação dos resultados obtidos. / The competitive environment in which firms operate is characterized by frequent changes in product demand and a necessity to reduce costs. To succeed against the competition, it is necessary to gain competitive advantage by improving the production process, providing faster responses to changes in demand and proper use of productive resources. In this context, the use of Advanced Planning and Scheduling software with custom programming rule allows improved planning and programming company towards the objectives mentioned. This study proposes a systematic development and deployment of custom programming rules, next it is presented a case study which detail the stages proposed in the systematic, from the understanding of the business requirement until the evaluation of results.

Planning, scheduling and real time optimization (RTO) are currently implemented by using different types of models, which causes discrepancies between their results. This work presents a single model of a crude distillation unit (preflash, atmospheric, and vacuum towers) suitable for all of these applications, thereby eliminating discrepancies between models used in these decision processes. Hybrid model consists of volumetric and energy balances and partial least squares model for predicting product properties. Product TBP curves are predicted from feed TBP curve, operating conditions (flows, pumparound heat duties, furnace coil outlet temperatures). Simulated plant data and model testing have been based on a rigorous distillation model, with 0.5% RMSE over a wide range of conditions. Unlike previous works, we do not assume that (i) midpoint of a product TBP curve lies on the crude distillation curve, and (ii) midpoint between the back-end and front-end of the adjacent products lies on the crude distillation curves, since these assumptions do not hold in practice. Associated properties (e.g. gravity, sulfur) are computed for each product based on its distillation curve. Model structure makes it particularly amenable for development from plant data. High model accuracy and its linearity make it suitable for optimization of production plans or schedules. / Thesis / Master of Applied Science (MASc)

Ph. D. Thesis / In order to compute more realistic production plans and schedules, techniques using nonlinear programming (NLP) and mixed-integer nonlinear programming (MINLP) have gathered a lot of attention from the industry and academy. Efficient solution of these problems to a proven ε-global optimality remains a challenge due to their combinatorial, nonconvex, and large dimensionality attributes. The key contributions of this work are: 1) the generalization of the inventory pinch decomposition method to scheduling problems, and 2) the development of a deterministic global optimization method. An inventory pinch is a point at which the cumulative total demand touches its corresponding concave envelope. The inventory pinch points delineate time intervals where a single fixed set of operating conditions is most likely to be feasible and close to the optimum. The inventory pinch method decomposes the original problem in three different levels. The first one deals with the nonlinearities, while subsequent levels involve only linear terms by fixing part of the solution from previous levels. In this heuristic method, infeasibilities (detected via positive value of slack variables) are eliminated by adding at the first level new period boundaries at the point in time where infeasibilities are detected. The global optimization algorithm presented in this work utilizes both piecewise McCormick (PMCR) and Normalized Multiparametric Disaggregation (NMDT), and employs a dynamic partitioning strategy to refine the estimates of the global optimum. Another key element is the parallelized bound tightening procedure. Case studies include gasoline blend planning and scheduling, and refinery planning. Both inventory pinch method and the global optimization algorithm show promising results and their performance is either better or on par with other published techniques and commercial solvers, as exhibited in a number of test cases solved during the course of this work. / Thesis / Doctor of Philosophy (PhD) / Optimal planning and scheduling of production systems are two very important tasks in industrial practice. Their objective is to ensure optimal utilization of raw materials and equipment to reduce production costs. In order to compute realistic production plans and schedules, it is often necessary to replace simplified linear models with nonlinear ones including discrete decisions (e.g., “yes/no”, “on/off”). To compute a global optimal solution for this type of problems in reasonable time is a challenge due to their intrinsic nonlinear and combinatorial nature. The main goal of this thesis is the development of efficient algorithms to solve large-scale planning and scheduling problems. The key contributions of this work are the development of: i) a heuristic technique to compute near-optimal solutions rapidly, and ii) a deterministic global optimization algorithm. Both approaches showed results and performances better or equal to those obtained by commercial software and previously published methods.

One of the major planning problems faced by medium and large manufacturing enterprises is the distribution of production over various (production) facilities. The need for cross-facility capacity management is most evident in the high-tech industries having capital-intensive equipment and short technology life cycle. There have been solutions proposed in the literature that are based on the lagragian decomposition method which separate the overall multiple product problem into a number of single product problems. We believe that multi-agent systems, given their distributed problem solving approach can be used to solve this problem, in its entirety, more effectively. According to other researchers who have worked in this field, auction theoretic mechanisms are a good way to solve complex production planning problems. This research study develops a multi-agent system and negotiation protocol based on combinatorial auction framework to solve the given multi-facility planning problem. The output of this research is a software library, which can be used as a multi-agent system model of the multi-product, multi-facility capacity allocation problem. The negotiation protocol for the agents is based on an iterative combinatorial auction framework which can be used for making allocation decisions in this environment in real-time. A simulator based on this library is created to validate the multi-agent model as well as the auction theoretic framework for different scenarios in the problem domain. The planning software library is created using open source standards so that it can be seamlessly integrated with scheduling library being developed as a part of the Advanced Planning and Scheduling (APS) system project or any other software suite which might require this functionality. The research contribution of this study is in terms of a new multi-agent architecture for an Advanced Planning and Control (APS) system as well as a novel iterative combinatorial auction mechanism which can be used as an agent negotiation protocol within this architecture. The theoretical concepts introduced by this research are implemented in the MultiPlanner production planning tool which can be used for generating master production plans for manufacturing enterprises. The validation process carried out on both the iterative combinatorial framework and the agent-based production planning methodology demonstrate that the proposed solution strategies can be used for integrated decision making in the multi-product, multi-facility production planning domain. Also, the software tool developed as part of this research is a robust, platform independent tool which can be used by manufacturing enterprises to make relevant production planning decisions. / Master of Science

Este trabalho tem como objetivo principal a proposição de um método de desenvolvimento de sistemas híbridos de planejamento e programação da produção para ambientes de manufatura enxuta que possuam alta variedade de itens, estruturas complexas, variabilidade de lead times e demanda flutuante. Nestes ambientes existe uma grande dificuldade na definição das estratégias para a adoção do sistema mais adequado de planejamento e programação da produção. A maioria das empresas acaba adotando um tratamento genérico de planejamento e programação para todos os itens. O método foi desenvolvido a partir de uma ampla revisão bibliográfica em torno de sistemas de planejamento, programação e controle da produção, de suas respectivas funções, dos desafios para os sistemas atuais, bem como dos princípios e das principais práticas e ferramentas enxutas. Em seguida, o método foi testado em quatro aplicações práticas nas quais a essência da discussão em torno de um sistema de planejamento e programação da programação migrou do tradicional conflito entre sistemas kanban versus MRP, puxar versus empurrar, para o desafio de se criar um ambiente no qual estes dois sistemas, juntamente com outros, devem coexistir em harmonia. / This work has as main goal to propose a method of developing hybrid systems for planning and scheduling for lean manufacturing environments that have high variety of items, complex structures, variability of lead times and fluctuating demand. In these environments there is great difficulty in defining the strategies to adopt the most appropriate system of planning and scheduling. Most companies just adopting a generic treatment planning and programming for all items. The method was developed from an extensive literature review around systems of planning and scheduling of production, their respective roles, the challenges to the current systems as well as the principles and practices of the major tools and dried. Then, the method was tested in four practical applications in which the essence of the debate on a system of planning and scheduling migrated from traditional conflict between kanban systems versus MRP, pull vs. push, to the challenge of creating an environment in which these two systems, along with others, must coexist in harmony.

Este trabalho tem como objetivo principal a proposição de um método de desenvolvimento de sistemas híbridos de planejamento e programação da produção para ambientes de manufatura enxuta que possuam alta variedade de itens, estruturas complexas, variabilidade de lead times e demanda flutuante. Nestes ambientes existe uma grande dificuldade na definição das estratégias para a adoção do sistema mais adequado de planejamento e programação da produção. A maioria das empresas acaba adotando um tratamento genérico de planejamento e programação para todos os itens. O método foi desenvolvido a partir de uma ampla revisão bibliográfica em torno de sistemas de planejamento, programação e controle da produção, de suas respectivas funções, dos desafios para os sistemas atuais, bem como dos princípios e das principais práticas e ferramentas enxutas. Em seguida, o método foi testado em quatro aplicações práticas nas quais a essência da discussão em torno de um sistema de planejamento e programação da programação migrou do tradicional conflito entre sistemas kanban versus MRP, puxar versus empurrar, para o desafio de se criar um ambiente no qual estes dois sistemas, juntamente com outros, devem coexistir em harmonia. / This work has as main goal to propose a method of developing hybrid systems for planning and scheduling for lean manufacturing environments that have high variety of items, complex structures, variability of lead times and fluctuating demand. In these environments there is great difficulty in defining the strategies to adopt the most appropriate system of planning and scheduling. Most companies just adopting a generic treatment planning and programming for all items. The method was developed from an extensive literature review around systems of planning and scheduling of production, their respective roles, the challenges to the current systems as well as the principles and practices of the major tools and dried. Then, the method was tested in four practical applications in which the essence of the debate on a system of planning and scheduling migrated from traditional conflict between kanban systems versus MRP, pull vs. push, to the challenge of creating an environment in which these two systems, along with others, must coexist in harmony.