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Changing a traditional company into a lean one is a very complex and time-consuming process that needs to be addressed in an appropriate way, otherwise the project of introduction of leanness into a company may fail on the one hand and even have a negative impact on business operations of the company on the other. When introducing a change, a step-by-step procedure leading to a progress may be of great help. The paper outlines a general procedure of leanness, an important part of which is a lean agent. A portfolio analysis is also used as a measure of leanness or as an indicator of the desired direction. The applied working methods were mainly active workshops and interviews with employees. The procedure has been tested on an example of a Slovene company; first, the existing situation is outlined, then the leanness steps taken according to the procedure and the final result after the first transition of the procedure.
Davorin Cimermančič; Janez Kušar; Tomaž Berlec. A procedure for the introduction of leanness into a company. Central European Journal of Operations Research 2021, 1 -31.
AMA StyleDavorin Cimermančič, Janez Kušar, Tomaž Berlec. A procedure for the introduction of leanness into a company. Central European Journal of Operations Research. 2021; ():1-31.
Chicago/Turabian StyleDavorin Cimermančič; Janez Kušar; Tomaž Berlec. 2021. "A procedure for the introduction of leanness into a company." Central European Journal of Operations Research , no. : 1-31.
In today’s highly dynamic and unpredictable project environment, companies need to be able to manage changes quickly and effectively, otherwise, the final product will not be current and will only go to waste. Traditional project management approaches that focus on planning are no longer efficient and companies are forced to adopt new ways of working. As a result, more flexible agile project management (APM) approaches have emerged over the last decades. Originally developed for the software industry, APM is now increasingly recognized and adopted also by other industry sectors. However, due to some discipline-specific differences, the adoption of APM by non-software companies is challenging and requires many adjustments and high financial input. While the larger organizations have sufficient resources to make such a transition, small and medium-sized enterprises (SMEs) generally cannot afford to do so, and therefore need alternative strategies to increase their agility and stay competitive on the global market. In this paper, we present a case study of a Slovenian medium-sized manufacturing company that implemented only certain APM practices separately and not as part of a structured APM methodology, and still managed to achieve significant benefits: improved communication, faster detection of discrepancies, more effective problem-solving and greater flexibility. The results also suggest that APM practices, even when implemented separately, positively impact project success in terms of both efficiency and stakeholder satisfaction, and can thus help in establishing an economically, socially, and environmentally more sustainable workplace.
Tena Žužek; Žiga Gosar; Janez Kušar; Tomaž Berlec. Adopting Agile Project Management Practices in Non-Software SMEs: A Case Study of a Slovenian Medium-Sized Manufacturing Company. Sustainability 2020, 12, 9245 .
AMA StyleTena Žužek, Žiga Gosar, Janez Kušar, Tomaž Berlec. Adopting Agile Project Management Practices in Non-Software SMEs: A Case Study of a Slovenian Medium-Sized Manufacturing Company. Sustainability. 2020; 12 (21):9245.
Chicago/Turabian StyleTena Žužek; Žiga Gosar; Janez Kušar; Tomaž Berlec. 2020. "Adopting Agile Project Management Practices in Non-Software SMEs: A Case Study of a Slovenian Medium-Sized Manufacturing Company." Sustainability 12, no. 21: 9245.
Companies have to assure their share on the global market, meet customer demands and produce customer-tailored products. With time and production line updates, the layout becomes non-optimal and product diversity only increases this problem. To stay competitive, they need to increase their productivity and eliminate waste. Due to a variety of products consisting of similar components and variants thereof, a huge number of various elements are encountered in a production process, the material flow of which is hardly manageable. Although the elements differ from each other, their representative elements can be defined. This paper will illustrate a methodology for searching representative elements (MIRE), which is a combination of the known Pareto’s analysis (also known as ABC analysis or 20/80 rule) and a calculation of a loading function, that can be based on any element feature. Results of using the MIRE methodology in a case from an industrial environment have shown that the analysis can be carried out within a very short time and this provides for permanent analysis, optimisation and, consequently, permanent improvement in the material flow through a production process. The methodology is most suitable for smaller companies as it enables rapid analysis, especially in cases when there is no pre-recorded material flow.
Jure Murovec; Janez Kušar; Tomaž Berlec. Methodology for Searching Representative Elements. Applied Sciences 2019, 9, 3482 .
AMA StyleJure Murovec, Janez Kušar, Tomaž Berlec. Methodology for Searching Representative Elements. Applied Sciences. 2019; 9 (17):3482.
Chicago/Turabian StyleJure Murovec; Janez Kušar; Tomaž Berlec. 2019. "Methodology for Searching Representative Elements." Applied Sciences 9, no. 17: 3482.
Customers require short delivery times and high quality products. Both requirements of customers can only be met if a company switches from a classically organized to a Lean Six Sigma production. Based on a value stream analysis that shows the size of the lead time and of process efficiency, overall equipment effectiveness and process efficiency allow us to determine a leanness index of a production process. The paper shows a measured procedure for the leanness of the production process based on a two-step portfolio analysis, consisting of a portfolio analysis of leanness for a production system and of a Lean Six Sigma process. The value of the leanness index and sigma process value in fact show the leanness of a six sigma production process. Portfolio analyses of leanness of the production process and the leanness of the Six Sigma process are shown in an example of the production of cooling covers.
Eva Jordan; Janez Kušar; Lidija Rihar; Tomaž Berlec. Portfolio analysis of a Lean Six Sigma production process. Central European Journal of Operations Research 2019, 27, 797 -813.
AMA StyleEva Jordan, Janez Kušar, Lidija Rihar, Tomaž Berlec. Portfolio analysis of a Lean Six Sigma production process. Central European Journal of Operations Research. 2019; 27 (3):797-813.
Chicago/Turabian StyleEva Jordan; Janez Kušar; Lidija Rihar; Tomaž Berlec. 2019. "Portfolio analysis of a Lean Six Sigma production process." Central European Journal of Operations Research 27, no. 3: 797-813.
The implementation of lean production in a company is a transformation of the whole company’s culture. To achieve such a lean culture, the role and support of management are decisive. This paper introduces a newly defined model and methodology with an interview guide which helps to distinguish a supportive from a non-supportive management team when introducing lean production, and helps to decide if a step needs to be repeated, improved, or the next step can be initiated. The methodology is especially suitable for small and medium-sized enterprises (SME’s), because of their lack of human resources, where this model was also tested.
Tomaž Berlec; Mario Kleindienst; Christian Rabitsch; Christian Ramsauer. Methodology To Facilitate Successful Lean Implementation. Strojniški vestnik – Journal of Mechanical Engineering 2017, 63, 457 .
AMA StyleTomaž Berlec, Mario Kleindienst, Christian Rabitsch, Christian Ramsauer. Methodology To Facilitate Successful Lean Implementation. Strojniški vestnik – Journal of Mechanical Engineering. 2017; 63 (7-8):457.
Chicago/Turabian StyleTomaž Berlec; Mario Kleindienst; Christian Rabitsch; Christian Ramsauer. 2017. "Methodology To Facilitate Successful Lean Implementation." Strojniški vestnik – Journal of Mechanical Engineering 63, no. 7-8: 457.
Primož Potočnik; Tomaž Berlec; Alojzij Sluga; Edvard Govekar. Hybrid Self-Organization Based Facility Layout Planning. Strojniški vestnik – Journal of Mechanical Engineering 2014, 60, 789 -796.
AMA StylePrimož Potočnik, Tomaž Berlec, Alojzij Sluga, Edvard Govekar. Hybrid Self-Organization Based Facility Layout Planning. Strojniški vestnik – Journal of Mechanical Engineering. 2014; 60 (12):789-796.
Chicago/Turabian StylePrimož Potočnik; Tomaž Berlec; Alojzij Sluga; Edvard Govekar. 2014. "Hybrid Self-Organization Based Facility Layout Planning." Strojniški vestnik – Journal of Mechanical Engineering 60, no. 12: 789-796.
Tomaž Berlec; Janez Kušar; Janez Žerovnik; Marko Starbek. Optimization of a Product Batch Quantity. Strojniški vestnik – Journal of Mechanical Engineering 2014, 60, 35 -42.
AMA StyleTomaž Berlec, Janez Kušar, Janez Žerovnik, Marko Starbek. Optimization of a Product Batch Quantity. Strojniški vestnik – Journal of Mechanical Engineering. 2014; 60 (1):35-42.
Chicago/Turabian StyleTomaž Berlec; Janez Kušar; Janez Žerovnik; Marko Starbek. 2014. "Optimization of a Product Batch Quantity." Strojniški vestnik – Journal of Mechanical Engineering 60, no. 1: 35-42.
Tomaž Berlec; Janez Kušar; Lidija Rihar; Marko Starbek. Selecting the Most Adaptable Work Equipment. Strojniški vestnik – Journal of Mechanical Engineering 2013, 57, 400 -408.
AMA StyleTomaž Berlec, Janez Kušar, Lidija Rihar, Marko Starbek. Selecting the Most Adaptable Work Equipment. Strojniški vestnik – Journal of Mechanical Engineering. 2013; 57 (6):400-408.
Chicago/Turabian StyleTomaž Berlec; Janez Kušar; Lidija Rihar; Marko Starbek. 2013. "Selecting the Most Adaptable Work Equipment." Strojniški vestnik – Journal of Mechanical Engineering 57, no. 6: 400-408.
Tomaž Berlec; Janez Kušar; Lidija Rihar; Marko Starbek. Selecting of the Most Adaptable Work Equipment. Strojniški vestnik – Journal of Mechanical Engineering 2013, 1 .
AMA StyleTomaž Berlec, Janez Kušar, Lidija Rihar, Marko Starbek. Selecting of the Most Adaptable Work Equipment. Strojniški vestnik – Journal of Mechanical Engineering. 2013; ():1.
Chicago/Turabian StyleTomaž Berlec; Janez Kušar; Lidija Rihar; Marko Starbek. 2013. "Selecting of the Most Adaptable Work Equipment." Strojniški vestnik – Journal of Mechanical Engineering , no. : 1.
The paper presents a procedure for predicting due date of production orders on the basis of past actual lead time data. A client for a particular production order will select the best bidder. It is rather risky to make a bid just on the basis of sales experience. A procedure is therefore proposed by which, on the basis of the actual lead times of operational and assembly orders processed in the company’s workplaces in the past, the expected lead time of a planned production order can be predicted. The result of the proposed procedure for predicting lead times is an empirical distribution of possible lead times for a production order. On the basis of this distribution, it is possible to predict the probable lead time of a production order, taking into account a confidence interval. Using the proposed procedure, the sales department can make a delivery time prediction for the customer of the planned production order. As an illustration of using the procedure for predicting lead times of production orders, a case study is presented: the lead time of a production order for a “linking element of an oil vent” was predicted; the tool is manufactured by a Slovenian company.
Tomaž Berlec; Marko Starbek. Predicting Order Due Date. Arabian Journal for Science and Engineering 2012, 37, 1751 -1766.
AMA StyleTomaž Berlec, Marko Starbek. Predicting Order Due Date. Arabian Journal for Science and Engineering. 2012; 37 (6):1751-1766.
Chicago/Turabian StyleTomaž Berlec; Marko Starbek. 2012. "Predicting Order Due Date." Arabian Journal for Science and Engineering 37, no. 6: 1751-1766.
Organizing and optimizing production in small and medium enterprises with small batch production and many different products can be very difficult. This paper presents an approach to organize the production cells by means of clustering-manufactured products into groups with similar product properties. Several clustering methods are compared, including the hierarchical clustering, k-means and self-organizing map (SOM) clustering. Clustering methods are applied to production data describing 252 products from a Slovenian company KGL. The best clustering result, evaluated by an average silhouette width for a total data set, is obtained by SOM clustering. In order to make clustering results applicable to the industrial production cell planning, an interpretation method is proposed. The method is based on percentile margins that reflect the requirements of each production cell and is further improved by incorporating the economic values of each product and consequently the economic impact of each production cell. Obtained results can be considered as a recommendation to the production floor planning that will optimize the production resources and minimize the work and material flow transfer between the production cells.
Primož Potočnik; Tomaž Berlec; Marko Starbek; Edvard Govekar. Self-organizing neural network-based clustering and organization of production cells. Neural Computing and Applications 2012, 22, 113 -124.
AMA StylePrimož Potočnik, Tomaž Berlec, Marko Starbek, Edvard Govekar. Self-organizing neural network-based clustering and organization of production cells. Neural Computing and Applications. 2012; 22 (1):113-124.
Chicago/Turabian StylePrimož Potočnik; Tomaž Berlec; Marko Starbek; Edvard Govekar. 2012. "Self-organizing neural network-based clustering and organization of production cells." Neural Computing and Applications 22, no. 1: 113-124.