ACS Applied Computer Science

  • Increase font size
  • Default font size
  • Decrease font size

vol. 5, no. 2,2009

ARRANGING TASKS OF THE LASER CUTTER USING THE DYNAMIC CLASSIFICATION IN CONDITIONS OF UNIT AND SMALL BATCH PRODUCTION

In conditions of unit and small batch production a very important role is played by time of product availability for the customer. Despite using modern management techniques setup time still play an important role in the production cycle time. In the examined companies the relation between rearmament times to processing times is still high. The above researches inspired the author to prepare the method of setup times’ reduction through proper arrangement of tasks in the operational production plan. Optimization of the daily production plans is based on two-level division of scheduling and arranging tasks. The method was validated in conditions of the production practice for unit and small batch manufacturing. An example of arranging tasks for the laser cutter was given. The presented method is one of elements of the computer aided expert system for SME.

ESTIMATING PRIME COSTS OF PRODUCING MACHINE ELEMENTS AT THE STAGE OF PRODUCTION PROCESSES DESIGN

Using methods of planning automating of production processes as well as artificial intelligence, the methods presented in this paper were constructed for identifying the set value of manufacturing process parameters, which are key to evaluating the costs of the designed elements. The proposed solutions were adapted for systems used under the conditions of unit and small-batch production.

PERSONALITY IN PROJECT MANAGEMENT METHODS

High work efficiency is required by today’s organizations. Besides of other factors it depends on the right allocation of employed workers to their duties. Assigning employees to the right activities isn’t an easy task, because the job efficiency and differences in human nature have to be considered simultaneously. Usually, the decision undertaken by the human resource (HR) manager is based on his subjective experience. In several cases, such solution results in negative reactions of employees, and may lead to conflicts occurrence. In order to avoid them the problem of allocation of the properly selected team (taking into account workers’ personality) to the project’s activity is of crucial importance. Its right solution can decrease risk of activity execution delay. So, it is assumed the project’s completion time depends both on physical and psychological features of employed workers. Experimental results presented illustrate this approach.

RAPID PROTOTYPING OF VIRTUAL PRODUCTION NETWORKS IN SMEs

Nowadays many companies, especially small and medium-sized enterprises (SMEs), specialize in a limited field of production. It requires forming virtual production networks of cooperating enterprises to manufacture better, faster and cheaper. Apart from that, some production orders cannot be realized, because there may not be a company of sufficient production potential. In this case the virtual production networks of cooperating companies can realize these production orders. These networks have larger production capacity and many different resources. Therefore it can realize many more production orders than only one of them. Such organization allows for executing high quality product. The maintenance costs of production capacity and used resources are not so high. The productivity is higher in all production systems in the network. The average costs of these systems are smaller and companies are more competitive.

ARTIFICIAL INTELLIGENCE TOOLS IN SIMULATION AND OPTIMIZATION OF PRODUCTION SYSTEMS

This article deals with solution developed as a cooperation of Industrial engineering department, University of Žilina and Central European institute of Technology (CEIT SK). Proposed solution involves simulation with support of virtual reality for searching of engineer-accepted manufacturing system state (so called "optimal"). Article includes basic information about evolution methods and genetic algorithms. Authors own algorithm, which is based on use of genetic algorithm, is used for optimization. Outcomes compares the speed of convergence of chosen Witness optimization algorithms and authors-developed algorithm. Comparison is presented on project from industrial praxis.

Page 1 of 2

  • «
  •  Start 
  •  Prev 
  •  1 
  •  2 
  •  Next 
  •  End 
  • »