The magic matrix as a smart scheduler
Identifieur interne : 002F16 ( Main/Exploration ); précédent : 002F15; suivant : 002F17The magic matrix as a smart scheduler
Auteurs : Gideon Halevi [Israël]Source :
- Computers in Industry [ 0166-3615 ] ; 1992.
Abstract
Production management (and scheduling) is based on the following basic assumptions: (i) routing is a constraint; and (ii) the problem is one of allocation of tasks. These assumptions and approach lead to problems of overload, underload, bottlenecks and disruptions. Many methods are proposed to solve these approach-oriented problems. Routing is the output of process planner's decisions. It is a decision taken at a too early stage of the production process, it hides the process planner's intentions, and as of today, it does not transfer technological data to production management. Thereby it imposes an artificial constraint on scheduling. To overcome these constraints a new approach to production management has been developed. It is called all-embracing technology and covers all aspects of the manufacturing process. It is based on a matrix format. In this paper only the scheduling stage will be presented. The approach incorporates technology in production management, thereby adding a new degree of freedom, and allowing to make crucial decisions at the right time and by the qualified professionals.The basic assumptions of the proposed approach are: (i) routing is a variable (to be decided upon by the magic matrix); do not separate technology from production management; and (ii) the problem is manufacturing. A matrix establishes a network of possible routings while deferring the decision of which path to take to a later stage. The production planning is divided into two levels, the planning level and the production level. The objective of the planning level is to set a product mix that is needed for a period. The production level objective is to carry out the plan (scheduling). To accomplish this objective the on-line shop floor scheduling uses the matrix to select a path, disregarding the path that was used at the planning level. Furthermore, the decision of a path may be changed after each operation. Simulations with the proposed scheduling method show that with the same resources an increase of throughput of up to 25% can be obtained. Furthermore this method reduces data bank sizes, computer load, computer size, response time, communication load and reports.
Url:
DOI: 10.1016/0166-3615(93)90020-2
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