Decision Making in Manufacturing and Services
Decision Making in Manufacturing and Services (p-ISSN 1896-8325, e-ISSN 2300-7087) is an interdisciplinary, international, peer-reviewed and open access journal. DMMS semiannually 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. DMMS's objective is to serve 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. The journal encourages a variety of methodological approaches to decision-making in manufacturing and services. The papers may be theoretical or empirical, analytical or computational, and may be based on a variety of disciplinary foundations such as management, economics, operations research, computer science, engineering, psychology, etc. The DMMS also publishes state-of-the-art reports by invited authors, critical reviews, and special issues devoted to particular topics. The electronic version of the journal is the primary one. There is no article processing charge (APC) for publication in the journal; it is entirely free of charge Articles are published in English only. All manuscripts submitted for publication are checked for similarity with other published works. For this purpose, we use: . Articles are distributed according to the terms of the Creative Commons CC-BY 4.0 License.
Task-Location Assignment Problem in Planning Horizon
Efficient task allocation in production environments is essential for optimizing resource utilization and minimizing operating costs. This paper proposes a Mixed-Integer Linear Programming (MILP) model for the Task-Location Assignment Problem in Planning Horizon, with the objective of minimizing total operating costs. Additionally, two heuristic algorithms – a greedy scheduling algorithm and a priority-based scheduling algorithm – were developed to generate feasible solutions quickly. Computational experiments were conducted using real-world production process data across various scenarios. The results indicate that the proposed MILP model achieves an average cost reduction of approximately 11% compared to the greedy scheduling algorithm and about 6% compared to the priority-based scheduling algorithm. The results demonstrate the practical value of mathematical optimization in reducing internal production supply costs while supporting the efficient allocation of production tasks to available locations.
Copyright (c) 2026 Decision Making in Manufacturing and Services https://creativecommons.org/licenses/by/4.0
Hybrid Optimization for Secure and Timely Medical Logistics: A Case Study in Burkina Faso
Transportation logistics plays a critical role in ensuring equitable access to medical supplies in low-infrastructure and insecure environments. This paper proposes a three-stage hybrid framework to solve a Vehicle Routing Problem with Safety and Time Windows (VRP-ST) in high-risk contexts. The methodology combines a Clarke–Wright savings heuristic for rapid initialization, an Ant Colony Optimization (ACO) metaheuristic to minimize a risk-adjusted distance objective, and Google OR-Tools to strictly enforce hard constraints, including vehicle capacities and delivery time windows. The approach is evaluated on a nationwide case study involving 44 healthcare centers in Burkina Faso. The results show a 19% reduction in total risk-adjusted distance (from 10,425 to 8,280 units) relative to the initial heuristic solution, together with improved fleet utilization. Beyond this case study, the framework provides a robust and fully feasible decision-support tool for medical logistics planning in crisis-affected regions. A sensitivity analysis under ±10% demand and risk-penalty perturbations confirms the stability of the solutions.
Copyright (c) 2025 Decision Making in Manufacturing and Services https://creativecommons.org/licenses/by/4.0
Integration of Quality Planning with the ProductDevelopment Process
Quality planning is a key element of product development, especially in automotive projects governed by Advanced Product Quality Planning (APQP) reference logic. The literature indicates that the main research gap is not the absence of APQP or quality planning methods, but the lack of a dedicated approach for assessing how mature APQP-oriented quality planning is cascaded and embedded across organisational layers. This article develops a conceptual model linking product development with product and process quality planning at the strategic, process, and operational levels. The study is based on a literature review, gap analysis, system analysis, and conceptual modelling. The contribution is the development of a three-layer integration model and the Quality Planning Integration Maturity Index (QPIMI), a matrix-based tool for maturity-oriented assessment. QPIMI is proposed as a complementary diagnostic layer, not as an alternative to APQP. The approach supports evidence-based self-assessment and provides a basis for further empirical validation.
How to Interpret AHP/ANP Application Results in a Really Meaningful Manner?
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.
Copyright (c) 2021 Decision Making in Manufacturing and Services https://creativecommons.org/licenses/by/4.0
A Hierarchical Coordination Framework for Municipal Solid Waste Collection Management under Uncertainty
Municipal solid waste collection systems require coordinated decisions across strategic, tactical, and operational horizons, yet the optimization literature remains fragmented across planning levels and often treats uncertainty only within isolated model formulations. This paper proposes a hierarchical coordination framework for municipal solid waste collection management under uncertainty. The framework is defined as an interface-based, modular coordination artifact composed of reusable optimization modules, standardized input–output interfaces, and an uncertainty layer that enables alternative evaluation perspectives without requiring a monolithic reformulation of the underlying models. The proposed architecture links long-term fleet transition and modernization decisions with tactical fleet sizing, allocation, and utilization, as well as detailed operational routing and scheduling. Its main contribution is conceptual and design-oriented: it formalizes the roles of decision modules, the logic of top-down decision propagation and bottom-up performance feedback, and the architectural conditions under which validated optimization models can function as parts of a reusable multi-level decision-support structure. By positioning uncertainty as an external evaluation layer, the framework provides a basis for future comparative assessment under deterministic, stochastic, and distributionally robust perspectives. The paper thus contributes a structured coordination logic for integrating previously isolated optimization models in municipal solid waste collection management.
Process Maturity Model for Improving Blood Donor Service Quality – Proposed Assumptions and Assessment Criteria
The article presents the assumptions and criteria for assessing the process maturity model developed to improve the quality of blood donor service in blood donation and blood therapy centres. The methodological basis was a literature review and case analysis of public blood service units, in cooperation with the National Blood Centre (NBC) in Warsaw. The research was conducted as part of the project ‘Improving the quality of management in blood donation and blood therapy centers’ implemented by the NBC in 2022–2023. The model, developed by the author as a logistics expert, is multidimensional and makes it possible to assess the level of process maturity of Regional Blood Center (RBC) It takes into account the specificity of operational activities and donor relations as key elements of the quality of medical services provided by the centres. The publication contains proposals for the practical use of the model as a tool supporting management and improving service standards.
The Use of Lean Tools in the Food Industry
Lean, as a concept focused on eliminating waste, optimizing processes, and creating customer value, has enjoyed widespread applications across numerous industries. However, its effective implementation requires adaptation to the specific characteristics of a given sector and enterprise. This article presents an evaluation and analysis of the use of Lean Management and selected Lean tools in an enterprise operating in the food industry. Based on a structured literature review, the paper outlines the origins, fundamental assumptions, and key tools associated with Lean Manufacturing. Subsequently, an empirical study based on a questionnaire survey was conducted among employees of a food industry company that has been applying the Lean Management concept for several years and systematically uses a range of Lean tools to optimize and improve its processes. The findings provided the basis for the formulation of conclusions confirming the applicability and effectiveness of the Lean Management approach in the food industry, as well as for identifying and evaluating the extent of the use of individual Lean tools. The results may serve as a starting point for further research and support practical implementations of Lean in food industry enterprises.
Adoption of Electromobility in Urban Transport in Poland - Cost-Benefit Trade-Offs and Decision-Making Challenges
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 evaluation, the study compares the purchase and operational costs of EVs and conventional cars across mini, compact, and premium market segments, taking into account factors such as energy consumption, fuel and electricity prices, annual mileage, and carbon emission levels. 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.
The Evolution of BPM Platforms towards Low-Code –New Opportunities and Challenges for Businesses and Software Providers
The current transformation of classic business process management (BPM) systems into innovative low-code platforms is changing the way companies can automate and implement business processes and applications. Low-code platforms enable rapid development of software solutions and allow business users to create and modify workflows or even small applications with minimal programming skills. This technology has a lot of advantages, including increased agility, cost savings, and faster time-to-market. However, it also introduces challenges such as integration difficulties and the need to upskill employees. On the other hand, from the perspective of software companies, developing low-code platforms presents a lot of new challenges compared to traditional applications. Building a stable and flexible environment requires advanced architecture planning, intuitive user interfaces, and a powerful application engine that is simple to use but still scalable. We should also not forget about security, modularity, reusability, and integration issues. Using a qualitative, descriptive research methodology along with a thorough literature review, conceptual analysis and case study this article explores the challenges behind the transition from BPM to low-code, its impact on business organisations and technology providers, and the critical factors for successful implementation.
Operations Research in Municipal Solid Waste Management: Decision-Making Problems, Applications, and Research Gaps
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.
What AHP/ANP Can Do for Six Sigma? A Short Literature Survey
Six Sigma offers a robust and widely applicable methodology for tackling practical decision-making challenges across various industries. Complementarily, the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) provide a universal framework for decision support in diverse applications. Given their inherent strengths, these methodologies appear to be a natural fit. However, it remains uncertain whether this synergistic potential is fully leveraged within current Six Sigma practices and its derivative methodologies. This paper presents a comprehensive literature survey to ascertain the extent to which Six Sigma practitioners utilize AHP/ANP. The findings from this survey will then be used to identify current trends and highlight existing gaps in harnessing the full potential of AHP/ANP within the Six Sigma framework.
Multidimensional Identification of Key Problems ofa Production Company
This paper presents the application of multi-criteria analysis to support decision-making in the manufacturing industry, where resources are limited and problems are multifaceted. The DEMATEL method is employed, in which experts assess the direct impacts of problems on one another. By applying a threshold to the total influence matrix and computing the prominence (s+) and relation (s–) indices, the method generates a cause-and-effect diagram that clearly distinguishes factors that act as primary causes from those that serve as effects. An empirical case study conducted at an automotive components company reveals that the key problems requiring priority attention are the limited use of modern methodologies (e.g., Lean Manufacturing), high employee turnover, and frequent machine downtime. The findings illustrate that while several issues are present, only a few exhibit substantial causal impacts that, when addressed, can lead to significant improvements across the organisation. All in all, this work provides a framework for identifying critical factors in industrial decision-making processes.
Critical Success Factors for Six Sigma Implementation – A Case Study From an Automotive Company Located in Poland
Six Sigma is a widely adopted method across many companies from different industries based in various locations in the world. As the proper implementation of Six Sigma is critical for the further success of the method in companies, researchers and practitioners are analyzing which factors play an important role in early stages of adaptation. This paper refers to Critical Success Factors (CSF) analyzed in various types of companies, industries and locations. Additionally, the paper brings the perspective of the problem from a company in the automotive sector of Poland. Survey studies on Critical Success Factors (CSF) for Six Sigma implementation were performed across engineering teams working on product development and process optimization. The summarized results show the perspective of Six Sigma practitioners on the most important factors, specific to the given sector and location. The findings offer valuable insights for managers who are defining Six Sigma implementation strategies and teams which are planning individual implementation steps. The results are important for companies in Poland but also can be generalized for any Six Sigma implementation practices.
Deadhead Minimization Problem in Multi-Depot Public Transport System
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.
Significant and Trivial Dependencies Separation in Data Tensor by the Projection Method
The problem of data structure analysis through their multidimensional representation as a d-dimensional tensor is considered to assess dependencies on influencing factors in the decision-making process. The higher-order Singular Value Decomposition (SVD) is developed as a d-SVD schema to identify significant and trivial dependencies. The d-SVD includes the SVD of the tensor reshaped as a matrix and the SVDs of reduced size of the previous SVD vectors reshaped as matrices. The entropy of the distribution of the Singular Values (SVs) of the vectors’ decomposition is used for the separation of the significant and trivial vectors, in contrast to the commonly used approach based on the magnitude analysis of SVs. The singular projection in the significant vector space in selected dimensions gives the tensor’s low-rank approximation without loss of information in comparison with the truncated SVD. The tensor projection on a vector subspace of reduced dimension can be obtained by using a part of the SVs and the corresponding vectors as an alternative to the commonly used averaging. It was shown that data prediction in the subspace of the significant vectors allows stable assessments of the predicted values to be obtained.
This special issue of "Decision Making in Manufacturing and Services" is devoted to the field of Business Process Management (BPM) and contains ten selected papers presented at the 5th Polish BPM Symposium. This event is part of a series of meetings bringing together the Polish BPM community, including researchers, business professionals, and educators involved in BPM. The field of BPM continues to develop actively and attracts significant interest, as demonstrated by the popularity of events such as the International Conference on Business Process Management, the 22nd edition of which was held at AGH University of Krakow in September 2024. This special issue of DMMS, as a direct outcome of the symposium, presents works by Polish authors and showcases the implementation of the process approach in Polish companies. It is a diverse collection of studies and case analyses that contribute to the ongoing discourse on Business Process Management and its applications across various industries. These papers offer valuable insights into both theoretical advancements and practical implementations, addressing key technological, organizational, and educational aspects of BPM. By publishing these contributions in English with open access, this volume helps to disseminate the achievements of the Polish BPM Symposia and contributes to the global BPM research and practice. Together, these contributions provide a comprehensive overview of contemporary BPM challenges and solutions, bridging the gap between research and practice. The studies included in this volume not only expand the theoretical foundation of BPM but also offer actionable insights for organizations aiming to optimize their processes and drive innovation in an increasingly complex business environment. As a Poland-based initiative, this issue is a direct outcome of the 5th Polish BPM Symposium, marking another step in making BPM more popular as a subject of research and more suitable for practical implementation. Furthermore, it contributes to the consolidation and strengthening of the Polish BPM community by bringing together researchers and practitioners dedicated to advancing BPM methodologies and their real-world applications.
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Analysis of Six Sigma Tools Utilization in Phases of DMAIC Cycle
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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Leveraging Business Process Management for Sustainable Transformation: Case Study of MECK Decarbonization Strategy
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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Use of integrated ECM/BPM platforms in financial, quality and HR processes – a case study of a large organization from the medical industry
This paper discusses the integration of two independently evolving fields in management and information technology: business process management (BPM), and enterprise content management (ECM). The paper’s objective is to highlight the advantages of integrating these fields – particularly from practical and technological perspectives. The analysis of the integration benefits is based on a case study of a project that was focused on digitizing financial, quality, and HR processes within a nationwide network of diagnostic laboratories. In this project, an integrated open-source ECM/BPM platform that combined the Camunda BPM and Alfresco ECM environments was used as the primary technological component. The analysis of the implemented processes showed that most of them were classified as content-/document-centric, thus necessitating the use of the standard content processing services that were embedded within the ECM systems during their execution. Furthermore, the content that was generated and shared within these processes was stored more efficiently and securely in the ECM repository. The final aspect that is discussed was the potential for creating a centralized content processing model across the organization by using the integrated ECM/BPM platform as the central component.
Process Knowledge Value Proposition in Business Process Management
Business process conceptual modeling focuses on studying process scenarios and mapping workflows as well as analyzing a business actor’s behavior. Taking the process-modeling techniques that have been presented in the literature into account, the author noticed a variety of notations that were applied to the process’s description. In addition, the values in the business-process models and the management-science literature have different interpretations. In this study, the author focused on process-value identification, interpretation, and visualization and aimed to provide literature surveys on process knowledge as well as on process value. However, the academic research background is followed by another qualitative approach to capture process value and emphasize the thoughts of the business actors in a process. Hence, the case-study analysis is supplemented by a literature survey. In this case study (concerning a publishing house), process knowledge was received through interviews with the publishing house’s main editor as well as through a study of discussions that were provided by the editorial committee members. Finally, the potential advantages of the studying of process value and some limitations and challenges for the identification and modeling of value are identified. By examples, the author revealed some values that are realizable in the business process and discussed them, i.e., relevance and rigor in the publishing process. The main contribution concerned identifying and visualizing business-process value through modeling techniques. The author strongly emphasized that, in the research process as well as in the research-result-dissemination process, relevance and rigor as values should be critical. Beyond this, the author presented how goal-modeling notation i* and ArchiMate notation can be combined with e3 value-modeling notation and which consequences arrived from this combination.
Technological and Managerial Aspects in the Context of Business Process Management and Optimization
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.
Optimizing Public Service Delivery Through Automated Stakeholder Interaction: Low-code BPM Implementation
For years, public institutions have been characterized by a complex and specific structure that requires the applications of bureaucratic procedures that are in accordance with the law and the professional preparations of officials. Nowadays, public institutions have high requirements for implementing intelligent IT systems, which allow the handling of documents in electronic form and the automatic flow of the information that is contained in them. This article presents a set of business processes that have been implemented in a public institution (dealing with the implementation of tasks in agricultural and food markets) that was performed in the BPMN notation. In addition to a description of the system, the article presents the positive impact of the implementation on the work of the authority. The article presents how business-process modeling and simulation support an enterprise in creating an integrated information-processing system. It concludes with a presentation of the effects and changes that have occurred in the authority following the implementation of a business-process-management system.
BPMN in Legislation on Example of Public Procurement Law – Case Study
The subject of the study was the use of BPMN in the creations and implementations of legal regulations on examples of projects that concern the reforms of public procurement law and supporting them with IT tools. The most important observation that resulted from the study is that any legal regulations that concern the proceedings are basically (business) information systems and, as such, can be reflected in BPMN as pools (participant). The method of carrying out the procedure itself can be represented using a business-process model that is recorded in BPMN notation in the form of a Collaboration diagram; on this, the “regulation” exchanges information (data) with the other entities that carry out the procedure. Precise BPMN recording ensures the unambiguity of a regulation and allows for an assessment of the effects of the regulation before its implementation. The models that were used at the analysis stage can be transformed into executable models using IT tools that support supervision over the implementation of the procedure in accordance with a given regulation; this ensures the full coherence of the regulation and its subsequent implementation (supported by IT tools). BPMN models can be an annex to the regulation and, thus, contribute to its better understanding. On the other hand, the ability to read BPMN models is becoming a core competence – not only for consultants and programmers but also for lawyers and those officials who carry out such proceedings in accordance with a given regulation.
Case study: Development of Employee Suggestion System at OKNOPLAST Manufacturing Company as Element of Process Improvement
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.
Improving Business Processes at mBank – Case Study on “Return Disposition Management” Process
The main objective of this article is to present a method for improving the business processes of a bank through an illustrative case study. The presented method enables financial institutions that operate in heavily regulated markets to combine a holistic view of business-process management (BPM) with a multi-faceted analysis of the effectiveness and risks of their implemented business processes, as well as to implement selected improvements that follow the banks’ project management standards. This method combines elements of BPM and project management, which allow for a continuous analysis of the implementations of changing financial regulatory requirements and emerging opportunities (including technological ones) while prioritizing any implemented changes considering the regulator’s imposed obligations, risk mitigation, efficiency of changes, and employee development.
Implementation of Active Learning in BPM Education
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.
Modeling the Market Value of a Product Based on New Technologies - Preliminary Tool Concept
Changes in the way market advantage is achieved and the emphasis on value creation that has been introduced by technological change are forcing companies to seek new and effective management tools when it comes to innovative activities; hence, the discussion and presentation of the conceptualization of such a decision-making model. Its basic premise is to take the technology life cycle as a determinant of the market diffusion of a product based on the use of new technologies. Consequently, a decision matrix is developed – one dimension of which is innovation measured by the dynamics of technical debt and the other by customer-perceived value. The product as an analytical object is considered as the sum of the utility functions while allowing for each utility function to originate from the use of a different technology (which is in an adequate phase of its life cycle). After presenting the theoretical model, an example of an analysis of a fictitious product is given, which is a device for cooling and printing food substances. The presented analysis example shows the practical possibilities of using the developed decision-making tool in the areas of the technological and marketing activities of the enterprise and, in particular, the design of new products or new utility functions.
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An E-sourcing Platform for Improving Communication and Optimizing the Supply Chains of Textile Companies
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At the economic scale of manufacturing companies, supply chains have been much more disrupted, which has often been justified by delays in delivery schedules. The results were considered to be harmful and had a negative influence on productive systems. By choosing the textile sector, our study began with an analysis of the information and communication systems of a limited number of companies; from the results of this analysis, we concluded that the fragility of these systems was the reason for the inabilities of certain supply chains to maintain their stability during the crisis. So, the solution to remedy this type of problem was to propose an e-sourcing platform that connects all of the companies that are active in this sector and those who are in direct contact with them to create a web network where the procurement procedures are similar – starting with the search for suppliers, and going as far as signing contracts online with a view of this research.
Application of Basic Machine-Learning Classifiers for Automatic Anomaly Detection in Shewhart Control Charts
In today’s dynamic technological environment, innovation plays a crucial role – especially for manufacturing enterprises that constantly strive to improve the quality of their products. This article examines the quality-management issue in a company producing car rims. It was identified that real-time quality control can sometimes be unreliable due to controller fatigue, leading to erroneous data interpretation or delayed responses to deviations in the production process. The study aimed to investigate the possibility of eliminating or significantly reducing these errors by employing a tool that is based on artificial intelligence. The article covers the preparation of training data, the training of classifiers, and the evaluation of their effectiveness in analyzing control charts in real time. The adopted hypothesis assumes that machine-learning classifiers can be effective methods of support for quality controllers. The research began with collecting measurement data from the machine and dividing it into training and test sets. The obtained results were evaluated using standard quality measures for machine-learning models. The results showed that the use of artificial intelligence can bring significant benefits in improving quality supervision in the production process of car rims.
Digital Transformation: Impact of Modern Technologies and Project Management on Optimization of Production Processes in Era of Industry 4.0
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.