Escalonamento do serviço laboratorial do Instituto dos Vinhos do Douro e do Porto, I.P.: uma heurística de apoio à decisão

Mestrado em Engenharia e Gestão IndustrialO presente projeto insere-se num serviço laboratorial onde são executados diversos tipos de análises de vinhos com o propósito de certificar e controlar os produtos da região do Douro. O projeto em estudo retrata um caso particular dos problemas de escalonamento, Flexible Job-Shop Scheduling Problem (FJSSP), com uma complexidade acrescida devido à diversidade de análises, equipamentos e rotas que coexistem no shopfloor. A metodologia utilizada para a resolução do problema em estudo compreende o desenvolvimento, e programação, de uma heurística construtiva, baseada na Teoria das Restrições, capaz de efetuar o escalonamento das análises tendo em conta as características específicas do laboratório. Pretende-se, através deste algoritmo, adequar o escalonamento à capacidade de resposta do laboratório, minimizando o makespan e, em última instância, permitir um aumento do nível de serviço a toda a fileira vitivinícola da Região Demarcada do Douro. Através da aplicação deste algoritmo, a empresa consegue uniformizar o processo de seleção de encomendas e executar um escalonamento da produção dimensionado para a capacidade do laboratório e ajustado às características intrínsecas de cada rota de produção, permitindo um aumento do throughtput do sistema.This project is part of a laboratory service where several types of wine analysis are performed with the purpose of certifying and controlling Douro products. The problem portrays a case of scheduling problems, Flexible Job-Shop Scheduling Problem (FJSSP), with increased complexity due to the diversity of analyzes, equipment and routes that coexist in shop floor. The methodology used to solve the problem under study comprises the development and programming of a constructive heuristic based on Theory of Constraints, that is capable of scheduling production considering the specific characteristics of the laboratory. Through this algorithm, it is intended to adapt the scheduling to the labs' capacity, minimizing the makespan and, in the end analysis, to allow an increase on the service level to the entire wine industry of Região Demarcada do Douro. Through the application of this algorithm, the company can standardize the order selection process and execute a production scheduling that is scaled to the laboratory capacity and adjusted to the intrinsic characteristics of each production route, allowing an increase of the system throughput

SUPPLY CHAIN SCHEDULING FOR MULTI-MACHINES AND MULTI-CUSTOMERS

Manufacturing today is no longer a single point of production activity but a chain of activities from the acquisition of raw materials to the delivery of products to customers. This chain is called supply chain. In this chain of activities, a generic pattern is: processing of goods (by manufacturers) and delivery of goods (to customers). This thesis concerns the scheduling operation for this generic supply chain. Two performance measures considered for evaluation of a particular schedule are: time and cost. Time refers to a span of the time that the manufacturer receives the request of goods from the customer to the time that the delivery tool (e.g. vehicle) is back to the manufacturer. Cost refers to the delivery cost only (as the production cost is considered as fi xed). A good schedule is thus with short time and low cost; yet the two may be in conflict. This thesis studies the algorithm for the supply chain scheduling problem to achieve a balanced short time and low cost. Three situations of the supply chain scheduling problem are considered in this thesis: (1) a single machine and multiple customers, (2) multiple machines and a single customer and (3) multiple machines and multiple customers. For each situation, di fferent vehicles characteristics and delivery patterns are considered. Properties of each problem are explored and algorithms are developed, analysed and tested (via simulation). Further, the robustness of the scheduling algorithms under uncertainty and the resilience of the scheduling algorithms under disruptions are also studied. At last a case study, about medical resources supply in an emergency situation, is conducted to illustrate how the developed algorithms can be applied to solve the practical problem. There are both technical merits and broader impacts with this thesis study. First, the problems studied are all new problems with the particular new attributes such as on-line, multiple-customers and multiple-machines, individual customer oriented, and limited capacity of delivery tools. Second, the notion of robustness and resilience to evaluate a scheduling algorithm are to the best of the author's knowledge new and may be open to a new avenue for the evaluation of any scheduling algorithm. In the domain of manufacturing and service provision in general, this thesis has provided an e ffective and effi cient tool for managing the operation of production and delivery in a situation where the demand is released without any prior knowledge (i.e., on-line demand). This situation appears in many manufacturing and service applications