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EN
According to requirements of the contemporary market the SME.s must offer the wide range of products adapted for individual requirements of the customer. This leads to manufacture in very short cycles and to the necessity of the individual production of unit and small batch condition. The manufacturing process requires documentation of the production. Very often, the documentation process and the time of its formation is limited. The article includes an analysis of the modern manufacturing systems and answers the question: how is possible to produce without having a documentation in paper form. The presented solution is used during the products manufacturing in the SMEs.
2
Content available remote Product family manufacturing based on dynamic classification
EN
According to requirements of the market a great number of small companies are forced to offer a wide variety of products and to frequently respond to the market with customized solutions. At the same time, the fast delivery of products is often key to winning orders. Recent developments in Information Technology have made product family manufacturing available for small companies. It is made possible by applying a class of software tools called product configurators which can be integrated with Enterprise Resource Planning (ERP) systems. This paper presents production management based on dynamic classification. High-variety production like mass customization is facing the challenge of effective variety management, which needs to deal with numerous variants of both product and process in order to accommodate diverse customer requirements. In high-variety production, in spite of applying modern management techniques, setup time still plays an important part in the production cycle time. The problem is not single change over time, but is in the quantity of changeovers required. This observation inspired the author to prepare a method of setup time reduction through the appropriate arrangement of tasks in the operational production plan. The appropriate arrangement of tasks means considering the similarity of parts from the point of view of operation carried out. The similarity of parts facilitates setup time reduction, which translates into smaller lot sizes, reduced in-process inventories, shorter lead time and higher throughput. The presented method is one of the elements of a computer aided management system for high-variety production. The method was validated in the conditions of best practice for unit and small batch production.
3
Content available remote Dynamic classification of tasks in condition of unit and small batch production
EN
In the process of unit and small batch production a very important aspect is the amount of time from production setup to availability to the customer. In spite of applying modern management techniques, setup time still plays an important part in the production cycle time. In the examined companies the relationship between changeover time to processing time was significant. The above research inspired the author to prepare a method of setup time reduction through the appropriate arrangement of tasks in the operational production plan. The appropriate arrangement meant considering the similarity of parts from the point of view of carried out operation. The similarity of parts facilitates setup time reduction, which translate into smaller lot sizes, reduced in-process inventories, shorter lead time and higher throughput. The method was validated in conditions of the production practice for unit and small batch production. The presented method is one of the elements of a computer aided management system for small and medium enterprises (SME).
EN
Since the production is aimed at fulfilling specific needs of demanding customers and not at filling warehouses, the production volume should reflect the volume of orders. In times of fight for the client every order has to be performed on time. What is more, in limes of fight for shortening the delivery cycle, meeting safe deadlines, that is distant in time, is not enough. Companies are forced to meet short deadlines with keeping the product price competitiveness condition. It is hardly possible without a proper, APS (Advanced Planning System) class, advanced planning support system. Currently, advanced planning systems arc coming into use, however (heir cost exceeds the possibilities of small and medium enterprises and algorithms used often require great customization to industries' needs and conditions of unit and small-hatch production. The paper has been drawn on the basis of research on overloads of moving bottlenecks in conditions of unit and small batch production in real conditions having a big number of resources and tasks. The methods used so far are not capable of finding the global optimum of such big data ranges. At present few working enterprises in conditions of unit and small batch production, especially in small and medium-sized enterprises (SME), are exploiting techniques of the production process optimization. For this reason computer tools for applying to the industrial scale arc needed. The above method basis on the data so far collected in computer systems. Results of preliminary research were introduced from applying the possibility of TOC (Theory of Constraints) to the industrial scale for reducing bottlenecks in unit and small batch production. The authors built a heuristic algorithm which could find solution good enough and based on TOC assumptions and verification of assumptions using tests in real production systems. The above method found application to the industrial scale, as extension of the ERP class system.
EN
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.
EN
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. To counterbalance fluctuations and inaccuracy of operational planning it is necessary to introduce the positive feed-back into the system in a form of registering of operations implementation.
EN
Tendencies in the development of systems of discrete production management in modern industrial companies are introduced in the thesis. The work range is confined to problems connected with unit and small batch production. There are described methods and techniques used in the optimization of management of machine elements manufacturing. There is found that modern management systems in conditions of unit and small batch production relative to decision making process require the data of operational area. Development of computer techniques enables to solve so stated problem. Decision related to acceptance or refusal of a client's order and related to the choice of the optimum variant of the manufacturing process run for the given order are the main subjects of the optimization. The work is supported by examples from real production.
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