Integrated Scheduling And Self-Reconfiguration Of Production Resources In Knowledgeable Manufacturing Environment

With the market competition intensify, the higher requirements for the ability to adapt fast changing market demands of manufacturing enterprises are brought forward. So how to respond to changing demands in a timely fashion has been a key problem urgently to be solved for manufacturing enterprises. Under this background, a new manufacturing mode named knowledgeable manufacturing arises at the historic moment, which places emphasis on description,excavation and discovery of the hidden intrinsic knowledge in manufacturing system. Furthermore,it could adjust system operational mode and parameters based on the new acquired knowledge, so as to keep the system in good operating condition all the time. The knowledgeable manufacturing system (KMS) which is built on the concept of knowledgeable manufacturing is a highly intelligent manufacturing system mainly characterized by self-adaptation, self-evolution and self-reconfiguration. The self-reconfiguration is committed to reconfiguring process route,production scheduling, production capacity distribution, production and purchase planning, material handling, structure of the production management system, etc. so as to respond quickly to changing requirements and minimize total production and reconfiguration cost.In this dissertation, the self-reconfiguration of KMS oriented to the production execution progress is developed. The optimization theory of self-reconfiguration is further improved. The research promotes the KMS shifts from management level to manufacturing execution level. The main tasks of the dissertation are summarized as follows:1. To meet demand changes,a self-reconfiguration of product process routes in KMS is studied.To minimize the work-in-process level and the number of process operations reassigned among the different machines without violating production rate, operation precedence, complete machining and operation-machine assign feasibility constraints, a mathematical model of process route self-reconfiguration is constructed. An improved chaotic non-dominated sorting genetic algorithm(IC-NSGA) is put forward. A Skew Tent map is adopted as chaotic sequence generator to perturb chromosome and avoid the search being trapped in local optimum. A decode algorithm based on operation precedence matrix and candidate machines set is designed to obtain a feasible operation sequence and processing machine sequence. A case study is presented to demonstrate the effectiveness of the model and the algorithm. The results provide the decision maker with several optional process route plans.2. Aircraft engine is assembled by plenty of assembly operations that have complex precedence constraints. When demand changes, manual adjustment cannot respond in time and make assembly efficiency low. To take aim at minimizing the total weighted sum of product completion time cost, the earliness penalty of operations, and the self-reconfiguration cost of teams and groups, an optimization model of aircraft engine assembly scheduling and self-reconfiguration is constructed. An alternate iterative approach is proposed to reconfigure of the schedule and the numbers of teams simultaneously. Properties of local optimal sequencing are proved. A decomposition algorithm based on local optimal sequencing is proposed and the scheduling problem is decomposed into single machine operations sequencing problem. A local backward inserting search strategy is designed. Once the optimal schedule is acquired, the teams are reconfigured by transferring them from workstations of lower utilization to those of higher utilization. Numerical experiments validate the effectiveness of the proposed model and algorithm.3. Aiming at the problem of low assembly efficiency and unreasonable worker assignment of an aircraft engine assembly line, an optimization model of tardiness scheduling and teams self-reconfiguration of KMS oriented to aircraft engines is constructed. A heuristic algorithm is proposed to optimize the schedule and the numbers of teams simultaneously. In the scheduling optimization layer, according to the characteristic of an aircraft engine with complex assembly precedence constraints, the properties of dominance relations of operations involving the objective of product tardiness optimization are proved and its corresponding operation adjustment algorithm is proposed. An initial assignment of operations on parallel assembly teams is given, and then a modified procedure is described. In the self-reconfiguration layer, the numbers of teams are adjusted on the basis of a workload balancing principle. The simulation experiments validate the effectiveness of the proposed model and algorithms.4. To solve the assembly problem of the aircraft engine with uncertain rework, an optimization model of rescheduling and teams self-reconfiguration of KMS oriented to aircraft engines assembly line is built, and an integrated optimization algorithm of both is proposed. In the scheduling phase,dominance relations of operations aiming at optimizing weighted completion cost are derived and applied to generating an initial operation sequence. Three neighborhood structures are defined. A variable neighborhood search (VNS) is used to optimize the assignment and the schedule of operations on parallel assembly teams. In the self-reconfiguration phase, the configuration of the assembly teams is generated according to the assembly line workload balancing without violating the assembly skills constraints, and then optimized by a tabu search (TS). The simulation experiments validate the effectiveness of the proposed model and algorithm.