1. Comparative analysis of human and artificial intelligence planning in production processesMatjaž Roblek, Tomaž Kern, Eva Krhač Andrašec, Alenka Brezavšček, 2024, original scientific article Abstract: Artificial intelligence (AI) has found applications in enterprises′ production planning
processes. However, a critical question remains: could AI replace human planners? We conducted a
comparative analysis to evaluate the main task of planners in an intermittent process: planning the
duration of production orders. Specifically, we analysed the results of a human planner using master
data and those of an AI algorithm compared to the actual realisation. The case study was conducted
in a large production company using a sample of production products and machines. We were able
to confirm two of the three research questions (RQ1 and RQ3), while the results of the third question
(RQ2) did not meet our expectations. The AI algorithms demonstrated significant improvement with
each iteration. Despite this progress, it is still difficult to determine the exact threshold at which AI
outperforms human planners due to the unpredictability of unexpected events. Even though AI
significantly improves prediction accuracy, the inherent variability and incomplete input data pose a
major challenge. As progress is made, robust data collection and management strategies need to be
integrated to bridge the gap between the potential of AI and its practical application, fostering the
symbiosis between human expertise and AI capabilities in production planning.
Keywords: artificial intelligence, machine learning, production processes, production planning, production scheduling
Published in DKUM: 04.12.2024; Views: 0; Downloads: 2
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2. Assembly line optimization using MTM time standard and simulation modeling—A case studyMatic Breznik, Borut Buchmeister, Nataša Vujica-Herzog, 2023, original scientific article Abstract: This study presents an approach to solving the assembly line balancing problem (ALBP) using the Methods-Time Measurement (MTM) time standard and simulation software. ALBP is a common problem in manufacturing where a set of tasks with fixed times must be assigned to a series of sequential workstations in order to minimize the total idle time and reduce the assembly cost per product. This study uses MTM, a widely used production process scheduling method, to create a new time analysis of an assembly process that was previously balanced using the Work-Factor method and time study. This literature review shows that there are a lack of combinations of updated time analyses with newer simulation approaches in the current literature, and this was the motivation for the present work. An assembly line simulation was performed using Simio software to evaluate different design options and operating scenarios. The results show that the use of MTM and simulation can help minimize idle time and improve assembly line performance, thereby reducing costs and increasing efficiency. This study shows that the approach of using MTM and simulation is effective in solving ALBP and is a useful tool for manufacturing companies to improve the performance of their assembly lines and reduce costs.
Keywords: optimization, production planning, assembly line, MTM time standard, simulation, industry 4.0
Published in DKUM: 23.05.2023; Views: 533; Downloads: 95
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4. A new method for determining extra time by considering ergonomic loads in the garment and metal working industriesVekoslav Verhovnik, Andrej Polajnar, 1993, original scientific article Abstract: The changing labour conditions in the garment and metal-working industries have led to the necessity of determining new extra times to establish the time standard. In this paper, a method of measuring stress and strain imposed upon the operator in new working conditions by determining the additional production coefficient is presented. The method gives criteria and grades to assess stress at the workplace. Physical stress (dynamic and static), thermal and visual stress, discomfort caused by noise, aerosols, gases and vapours, and the stress due to monotony are assessed. The stresses are expressed by ecological, physiological and psychological indexes. The indexes are pondered. Ponderation includes the factor of the magnitude and the time of exposure to stress. Ponderation is expressed by the number of points, the total being an adequate presentation of the stresses. Stress and strain decrease the working performance of the operator. Therefore they must be included in the standard to compensate for the operator's lower working efficiency due to physical and psychological strain at the workplace, Short breaks and stops allowed during work enable the operator to perform work tasks without getting excessively tired. The necessary correction of the production time is made by applying the ergonomic coefficient Ker.
Keywords: job analysis, production planning, stress assessment, time study, working conditions, working environment
Published in DKUM: 30.03.2017; Views: 1218; Downloads: 169
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5. A model of simulation environment for prediction and optimisation of production processesIgor Drstvenšek, Mirko Ficko, Ivo Pahole, Jože Balič, 2004, original scientific article Abstract: Paper describes means and methods for computer based optimisation of production processes using a new approach based on technological database (TDB) with genetic algorithm incorporated into a database management system (DBMS). The TDB serves as a store of tools and machine tools from which they can be assigned to different work operations. Work operations are basic entities of orders placed into queues. The goal of the model is to find available resources from the TDB in order to empty the queue in shortest time with lowest costs. To this purpose the model consist the technological database whose DBMS includes a genetic algorithm based optimiser. It checks the orders queue and searches for appropriate combinations of tools and machine tools from the TDB, which can be combined into needed work operations. It also performs an optimisation of time and costs according to so called static parameters of tools and machine tools.
Keywords: production processes, simulation, process planning, technological databases, genetic algorithms
Published in DKUM: 01.06.2012; Views: 1875; Downloads: 104
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