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DECISION MAKING IN MANUFACTURING AND SERVICES

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New!   Aktualny wolumen: Special Issue: Business Process Management (2024)

Decision Making in Manufacturing and Services is an interdisciplinary, international, peer-reviewed and open access journal. DMMS annually publishes papers of interest to the entire decision-making community, including academic and industry researchers and decision makers working at the interface of research and implementation in manufacturing and services.

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Now showing 1 - 10 of 152
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    Item type:Article, Access status: Open Access ,
    Adoption of Electromobility in Urban Transport in Poland – Cost-Benefit Trade-Offs and Decision-Making Challenges
    (Wydawnictwa AGH, 2021) Wiśniowski, Wojciech
    Electromobility is increasingly recognized as a cornerstone of sustainable urban transport strategies. This paper presents an analysis of selected economic, environmental, and infrastructural implications of transitioning from internal combustion engine vehicles to electric vehicles (EVs) in urban settings. Through a cost-benefit analysis, the study compares the purchase and operating costs of EVs and conventional cars across mini, compact, and premium market segments, accounting for factors such as energy consumption, fuel and electricity prices, annual mileage, and carbon emissions. The development and expansion of charging infrastructure, along with the integration of smart grid solutions and energy storage capabilities, are examined in the context of meeting the growing demand from a rising fleet of EVs. Additionally, the paper analyzes changes in urban mobility behaviors, highlighting the shift toward shared mobility and ecomobility, and discusses how these trends can reshape urban transportation to improve quality of life and reduce environmental impacts. Drawing on current trends, national electromobility development plans in Poland, and international best practices, the study identifies challenges and enablers for policymakers and decision-makers in the transportation and energy sectors, highlighting the need for coordinated planning and policy support to ensure the long-term viability and sustainability of electromobility in urban environments.
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    Item type:Article, Access status: Open Access ,
    How to Interpret AHP/ANP Application Results in a Really Meaningful Manner?
    (Wydawnictwa AGH, 2021) Ginda, Grzegorz
    Final decision recommendations rely heavily on ranking Decision-Making Units (DMUs), often achieved using Saaty’s Analytic Hierarchy/Network Process (AHP/ANP). AHP/ANP provides precise overall priority scores which decision-makers commonly treat as definitive for ranking purposes. This reliance means that even minimal numerical differences between DMUs are used to determine the final selection. However, this strict adherence to tiny numerical distinctions – disregarding the actual degree of difference – is problematic. Practically, it risks rejecting DMUs whose performance is only slightly inferior, methodologically, it contradicts the qualitative nature of the input (pairwise comparisons) with the quantitative output. This tension raises the question of achieving an adequate qualitative interpretation of the quantitative rankings. To resolve this, the paper proposes clustering approaches to help decision-makers reliably group and discriminate among similar DMUs. These methods aim to justify more informed choices by avoiding spurious precision. The approaches were tested using two diverse decision cases. The results are promising and indicate that these clustering techniques can be useful under certain specific circumstances.
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    Item type:Article, Access status: Open Access ,
    Operations Research in Municipal Solid Waste Management: Decision-Making Problems, Applications, and Research Gaps
    (Wydawnictwa AGH, 2021) Gdowska, Katarzyna
    Municipal Solid Waste Management (MSWM) represents a complex, multi-level decision domain that involves strategic, tactical, and operational planning under economic, environmental, and social constraints. This paper reviews the state of Operations Research (OR) applications to MSWM. The analysis encompasses optimization, simulation, metaheuristic, and hybrid approaches that address decision problems ranging from facility siting and capacity expansion to routing and scheduling. The study classifies OR contributions across decision levels, identifying methodological patterns and dominant model types such as mixed-integer programming, metaheuristics, and simulation-optimization frameworks. Despite significant progress in optimization and the integration of sustainability, critical gaps remain in uncertainty modeling, system-wide integration, and data-driven decision support. Deterministic formulations prevail at the strategic and tactical levels, while uncertainty is mainly explored in operational routing. Cross-level coordination among infrastructure planning, fleet design, and daily operations remains underdeveloped. Furthermore, persistent data scarcity and the limited incorporation of behavioral factors constrain the practical applicability of OR models. The review concludes with a research agenda that advocates for multi-level, uncertainty-aware, and dynamic optimization frameworks, supported by standardized data infrastructures and behavioral insights.
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    Item type:Article, Access status: Open Access ,
    Analysis of Six Sigma Tools Utilization in Phases of DMAIC Cycle
    (Wydawnictwa AGH, 2021) Soliński, Bartosz
    Six Sigma has been developed and successfully used in many organizations for many years. The use of Six Sigma in process-improvement requires the systematic and disciplined use of specific tools and techniques in the DMAIC cycle. The DMAIC cycle includes five phases: Define, Measure, Analyze, Improve, and Control this is one of the most popular Six Sigma improvement cycles that are used in improving existing processes. When improving processes in accordance with the DMAIC cycle, it is important to have knowledge of the tools and techniques that are used and the ability to select them for the specifics of a project and the appropriate phases of the cycle. This article critically reviews the literature on the use of individual tools in the appropriate phases of the DMAIC cycle and uses a semi-structured interview method with specialists in the field of using Six Sigma. The obtained results of the analyses can contribute to the study of the validity of using individual tools and techniques for the effective use of Six Sigma and provide a useful comparative review for theoreticians and practitioners who want to use the appropriate tools in the DMAIC cycle.
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    Item type:Article, Access status: Open Access ,
    Deadhead Minimization Problem in Multi-Depot Public Transport System
    (Wydawnictwa AGH, 2021) Szczyrbak, Robert
    This paper addresses a vehicle scheduling problem in the public transport system of Krakow, Poland. The primary objective is to develop and evaluate a mathematical model for assigning bus schedules to depots in a way that minimizes non-revenue (deadhead) kilometers. The proposed model, referred to as the Deadhead Minimization Problem in Multi-Depot Public Transport System (DMPMDPTS), seeks to reduce the total distance that is traveled by vehicles from their home depots to the starting points of their first scheduled routes and from the final terminals back to their depots. The model assumes fixed-route structures and known deadhead distances between terminals. Real-world data that was based on the Krakow Municipal Transport (KKM) was used to validate and verify the model. The optimization model was implemented in AMPL and solved using the GLPK Integer Optimizer (v4.43). Computational experiments were conducted across multiple cases that differed in their constraints and parameters in order to assess the model’s flexibility and performance. In all of the cases, optimal solutions were obtained in brief computation times. Compared to the existing operational schedules, the model consistently reduced deadhead kilometers. Case 1 achieved improvements without altering the numbers of vehicles per depot, while Case 2 led to further reductions of the costs of redistributing vehicles among depots, resulting in a less-balanced load structure. These findings demonstrated the model’s potential for supporting decision-making in depot allocation within public transport operations.
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    Item type:Article, Access status: Open Access ,
    Leveraging Business Process Management for Sustainable Transformation: Case Study of MECK Decarbonization Strategy
    (Wydawnictwa AGH, 2024) Szelągowski, Marek; Berniak-Woźny, Justyna; Zawalich, Beata; Radziszewski, Bartosz
    The heating sector is a critical focus for climate-change mitigation, as it accounts for 40–50% of global energy consumption and remains a major source of greenhouse gas (GHG) emissions. Miejska Energetyka Cieplna sp. z o.o. (MECK), a municipal heating company in Poland, faces an urgent need to undergo green transformation in order to comply with the Corporate Sustainability Reporting Directive (CSRD) and European Sustainability Reporting Standards (ESRS). This study aims to demonstrate how business process management (BPM) can be effectively applied to support MECK’s transition toward sustainable practices, ensuring its compliance with CSRD and ESRS requirements while fostering long-term profitability and competitiveness. Through the application of BPM, MECK has successfully embedded sustainability into its operations; key achievements have included developing actionable insights for process improvements, decarbonizing operations, reducing waste, creating new sustainable products, and adhering to CSRD and ESRS reporting standards. These efforts have enhanced MECK’s ability to secure long-term profitability while significantly improving its environmental sustainability. This case study highlights the pivotal role of BPM in enabling heating companies to meet regulatory requirements and advance their sustainability agendas. MECK’s experience underscores the importance of data quality, transparency, process optimization, and continuous improvement as foundational elements for achieving sustainability goals.
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    Item type:Article, Access status: Open Access ,
    Implementation of Active Learning in BPM Education
    (Wydawnictwa AGH, 2024) Grzesiak, Marzena
    The challenges that are faced by BPM educators are not only related to the evolution of the BPM concept and technological trends but also to the changing expectations and attitudes of students as well as the requirements of the labor market. Active learning promotes the better memorization and understanding of even tricky issues. Active-learning methods are increasingly being implemented, and their effectiveness is being studied in numerous scientific studies. Many studies have confirmed that better learning outcomes are achieved through active learning. Implementing flipped learning in a previous academic year and supplementing it with other active methods in the following year allowed for course improvements; students showed more outstanding commitment and satisfaction with the classes. The introduction of changes to the Business Process Modeling and Process Management courses was dictated by, among other things, the desire to adapt to the postulates that have been developed in the BPM educator community regarding the scope of the knowledge and the skills that were transferred within the courses. The changes concerned both lectures (reviews and updates of content, abandonments of the form of administration) and the laboratory (changes of program, preparations for certification). The conclusions from the observations of the pilot implementation of the changes in the courses constituted the basis for refining the materials and methods in the next academic year.
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    Item type:Article, Access status: Open Access ,
    Digital Transformation: Impact of Modern Technologies and Project Management on Optimization of Production Processes in Era of Industry 4.0
    (Wydawnictwa AGH, 2024) Stelmach, Adrian
    This article explores the impacts of digital transformations and new technologies in industrial sector (particularly through the Fourth Industrial Revolution) on optimizing production processes. Characterized by key technologies such as the Internet of Things (IoT), big data analytics, artificial intelligence (AI), blockchains, and advanced robotics, Industry 4.0 has significantly shaped modern manufacturing management. IoT enables autonomous communications between machines and equipment, providing real-time insights into production parameters and enabling predictive maintenance, and big data plays a vital role by analyzing the large volumes of data that are generated by these devices, thus supporting informed management decisions. AI and machine learning help automate complex tasks, optimize production schedules, and improve product quality through real-time adjustments. Blockchain enables decentralized and secure data recording, which is particularly useful in supply-chain management. Advanced robotics increases production speed and accuracy, thus reducing labor costs and mitigating any risks that are associated with hazardous tasks. Integrating these technologies requires strategic planning, including identifying key challenges, conducting pilot projects, integrating with existing IT and OT systems, and managing organizational change. Measuring the effectiveness of Industry 4.0 implementation should involve well-defined key performance indicators (KPIs) and return-on-investment (ROI) analysis. The primary challenges that are associated with adopting Industry 4.0 include the alignment of technology with specific business needs, employee resistance to change, and hidden costs of implementation. In summary, industrial transformation offers opportunities for companies to optimize production processes, reduce costs, and increase competitiveness in the global marketplace. However, a careful approach is necessary to maximize efficiency, foster innovation, and secure long-term success in an increasingly digitalized world.
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    Item type:Article, Access status: Open Access ,
    Case Study: Development of Employee Suggestion System at OKNOPLAST Manufacturing Company as Element of Process Improvement
    (Wydawnictwa AGH, 2024) Męcfel, Emilia
    This case study is focused on the development of the employee suggestion system at OKNOPLAST, a window joinery company. Based on the principles of the Kaizen philosophy, this system allows employees to make suggestions for improving the company’s production processes and their work environment. In the course of the analysis, a decline in the number of suggestions that were made and a reduced rate of their acceptance were identified, which indicated the need to get to the root causes of this phenomenon using lean methodology and elements of business-process management (BPM). In response to these challenges, measures were taken that included spreading awareness among managers, promoting the employee suggestion system (ESS), training new employees, and providing technical and analytical support for process engineering; these increased the number of submitted and accepted suggestions. Visualizations of the results and transparent reports were used, which contributed to an increase in the number of submitted and successful applications. As a result, there was an increase in the acceptance rate and employee involvement in the continuous improvement process. The study showed that lean and Kaizen methods had positive impacts on the company’s organizational culture and process efficiency. The results suggested that similar solutions could be successfully adapted in other manufacturing companies regardless of the industry. The study’s conclusions underscore the importance of engaging employees and supporting their initiatives, which can be key to achieving long-term benefits and improving performance.
  • thumbnail.journal.alt
    Item type:Article, Access status: Open Access ,
    Technological and Managerial Aspects in Context of Business-Process Management and Optimization
    (Wydawnictwa AGH, 2024) Rudolf, Łukasz; Roszak, Marek
    This article presents an original business-process-management (BPM) approach that integrates modern information technologies with managerial methods to enhance operational agility and organizational adaptability in a dynamic environment. The findings indicated that a harmonious integration of diverse information technologies with managerial methods significantly improved the execution of processes and enhanced organizational efficiency in achieving strategic objectives. A two-stage analysis was conducted, including a detailed review of key tools and strategies that supported essential business processes such as production, distribution, customer service, and order processing. Subsequently, the interdependencies among these processes were assessed, thus analyzing their impacts on operational flexibility and fluidity. The results suggested that an integrated approach that combines modern information technologies with managerial methods leads to significant improvements in performance, shorter lead times, optimized resource utilization, and faster responses to changing market demands. This study provides practical insights for those organizations that seek to maximize the benefits of digitalization and implement proven managerial methods to improve operational outcomes and achieve sustainable competitive advantages amid increasing competition and dynamic market changes.