Suhoruckov Dmitry Viktorovich

Master's thesis subject: Optimization of the industrial technological systems in mechanical engineering by using the genetic algorithms

Scientific adviser: Sekirin Alexandr Ivanovich

Final readiness of this work is January 2007. The full text you can receive get at the author.

Introduction

     A flexible manufacturing system (FMS) is a production system consisting of a set of identical and/or complementary numerically controlled machines which are connected through an automated guided vehicle (AGV) system. Since FMS is capable of producing a variety of part types and handling flexible routing of parts instead of running parts in a straight line through machines, FMS gives great advantages through the flexibility, such as dealing with machine and tool breakdowns, changes in schedule, product mix, and alternative routes. Flexible manufacturing is of increasing importance in advancing factory automation that keeps a manufacturer in a competitive edge.
     While FMS offers many strategic and operational benefits over conventional manufacturing systems, its efficient management requires solutions to complex process planning problems with multiple objectives and constraints. The aim of process planning is to develop a cost effective and operative process plan over the planning phases. Decisions about the process planning problem have to be made before the start of actual production, and consists of organizing the limited production resource constraints efficiently. Generally, the process planning includes routing optimization, equipment optimization and machine optimization (Tempelmeier and Kuhn, 1993).
     There are a lot of works devoted to a problem of operative management in discrete manufactures. Some control systems of flexible manufacturing systems are developed and introduced.
     Traditionally, the process planning has been solved by a process planner based on one’s experience without considering the dynamic characteristics of shop floor and market situations, such an aproach brings an error into an optimality of management. Further, a part is associated with a fixed or static process plan consisting of an ordered sequence of operations. However, the traditional methodologies are not suitable in flexible environment, because the methodologies have a few constrains in order to cope with dynamic situations of flexible environment.
     Therefore, it is obviously, that the problem of the optimum schedule development is an actual problem today.

The aim of master’s work

     The aim of my master’s work is to increase the FMS operational efficiency in mechanical engineering by search the suboptimum work based on the chosen criteria schedule on two levels: Job shop level and production level.
     Flexible Job Shop Schedule problem consists in the following: it is necessary to define the sequence of details in manufacture and the sizes of parties in the FMS with the set technological routes of details processing, so that the criterion of schedule quality aspired to an extremum.
As a whole the essence of master’s work is:

1. It is necessary to prepare algorithm for Job Shop optimization The possible criteria’s of the optimization of the schedule at the Job shop level are:

   • Minimization of the cycle duration;

   • Equipment loading maximization

   • "Just in time" - by the minimal deviation from directive term of release

   • Min quantity of readjustments

   • Directive priority;

   • The nearest term of readiness

2. It is necessary to prepare algorithm for schedule optimization on the production level, the possible criteria’s of the optimization are:

   • " just in time" - by the minimal deviation from directive term of release

   • Minimization of the orders production time;

3. Considering the practical manufacturing environments, my approach is based on using multiobjective evolutionary algorithm for solving this problem on two levels.

4. I propose the module of the specified optimization of the process planning problem in the flexible manufacturing systems

Prospective scientific novelty

1. The modified genetic algorithm adapted to solve a specialized problem of Flexible Job Shop Schedule problem on two levels;

2. The FMS model is supposed to use for maintenance of calculation the function criterion for the set of chromosomes to ormation the suboptimum schedule on two levels.

Prospective practical value

Work optimization on two levels due formation the optimum schedule based on the chosen criterion will allow to make the analysis of bottlenecks of manufacture and increase the overall performance of FMS.