INVOLVEMENT OF EMPLOYEES IN OPERATIONAL PLANNING OF MANUFACTURING ENTERPRISES: LATVIA EXPERIENCE

The main feature of teamwork is a common goal, and the involvement of employees is essential to its achievement. In a wider scope, it is understood not only by the involvement of employees in decision-making but also as the involvement of employees in operational planning and strategic issues. Research aim is to find out whether the involvement of employees in decision-making, goal setting and planning is inherent in manufacturing enterprises. According to a survey of 268 different level employees of 25 manufacturing enterprises in Latvia, it was found out that involvement of all employees in the decision-making process is not perceived by the enterprises` performance and strategic planning, and the involvement of employees in decision-making and goal setting can only be seen within the department. Keywords: decision-making, employee involvement, goal setting, operational planning, manufacturing enterprise, teamwork

Laser Projection Positioning Improving at a Machine- Building Manufacturing Enterprise Method

The goal of this work is to research a possibility of laser projection system adaptation to a machine-building manufacturing enterprise. A model example of the use of a computer vision system in production is the task of reducing the labor intensity of installing welded elements on a product, reducing the production time, and reducing the cost of work. A formal statement of the problem is given - to use a laser projection system in the conditions of assembly and welding production for positioning welded elements on the main product with respect to dimensional accuracy. For experimental research, a section of a machine-building production enterprise with a pre-defective product and welded elements was used. The research took place in two stages. As a result of the research, the results were obtained, confirming the efficiency of the method.

Reducing transaction costs through possible models of the opportunistic behavior of suppliers

Subject. The article discusses the issues of reducing transaction costs with respect to the opportunistic behavior of suppliers. Objectives. The study reveals forms and constituents of opportunism, analyzes possible model for the opportunistic behavior of supplier, illustrating the practical example. We suggest how transaction costs of manufacturing enterprises should be reduced. Methods. The methodological framework comprises general methods of analysis, synthesis, deduction, induction. We used articles and monographs of the Russian and foreign scholars, and data of manufacturing enterprises in machine building and metallurgy, which authors gained as part of their professional career. Results. Reviewing proceedings of foreign and national researchers on transaction costs with respect to the opportunistic behavior of supplier, we analyzed forms and constituents of opportunism. Models of suppliers’ opportunistic behavior are studied in terms of transaction costs incurred by the manufacturing enterprise, which performs orders for their suppliers. We suggest what should be done to prevent opportunism. We also revealed key strategies for responding to the opportunistic behavior of suppliers, which pursue lower transaction costs of manufacturing enterprises. Conclusions and Relevance. Preventing opportunism, manufacturing enterprises make their relations with suppliers more reliable and effective, thus reducing transaction costs in procurement. It is noteworthy that opportunism prevention activities should be undertaken if their cost is lower than the losses due to opportunism.

An Approach for Chart Description Generation in Cyber–Physical–Social System

There is an increasing use of charts generated by the social interaction environment in manufacturing enterprise applications. To transform these massive amounts of unstructured chart data into decision support knowledge for demand-capability matching in manufacturing enterprises, we propose a manufacturing enterprise chart description generation (MECDG) method, which is a two-phase automated solution: (1) extracting chart data based on optical character recognition and deep learning method; (2) generating chart description according to user input based on natural language generation method and matching the description with extracted chart data. We verified and compared the processing at each phase of the method, and at the same time applied the method to the interactive platform of the manufacturing enterprise. The ultimate goal of this paper is to promote the knowledge extraction and scientific analysis of chart data in the context of manufacturing enterprises, so as to improve the analysis and decision-making capabilities of enterprises.