Production systems are stopped due to malfunctions such as rotting equipment, imbalance of rotating parts, and high vibration, which leads to loss of customers, reduction of market share and unemployment of personnel. In this research, using the absorbing Markov process, a mathematical model is formulated to analyze the maintenance policy of the production process, through which one of the four states of new, old, or failure due to deterioration or sudden failure can be allocated to the machine. It is assumed that the machine changes from one state to another with different probabilities, which are determined using a discrete Markov chain. The different maintenance policies can be analyzed to minimize the average production cost. The mathematical model is obtained using discrete Markov chain equations, and the optimal maintenance and repair policy can be analyzed by considering all types of costs, including maintenance, production, and failure costs, so that the average cost of the production process can be minimized.

In this paper, we propose a new confidence interval (CI) for the population mean based on robust estimators, which involves the application of the winsorized modified one-step M-estimator (WMOM) and winsorized standard deviation (WSD). The proposed method is modified for the Student’s t confidence interval CI under the non-normal distribution. The performances of the proposed confidence interval were evaluated via a Monte-Carlo simulation study by considering the coverage ratio (CR) and the average length (AL) as performance criteria. The simulation study results show the superior performance of the proposed confidence interval (CI) over the classical parametric Student’s t for data from a non-normal distribution. Two real data sets were analyzed, and the results agree to some extent with those of the simulation study. The results confirm the suitability of the proposed CI estimator for both normally and non-normally distributed data.

This study investigates the organizational culture and lean readiness using the Organiza tional Culture Assessment Instrument (OCAI) and Lean Culture Assessment Model (LCAM) to implement lean for improving productivity in one of the Indian Micro, Small, and Medium Enterprises (MSMEs). The OCAI study results found that the organization has a family-style corporate culture and horizontal leadership. LCAM results showed that the company’s score on lean readiness is very low. Further, study through interaction with key organizational personnel revealed that the day-to-day operations were cluttered and lacked direction. The diagnostic study helped identify the cultural issues and problems of the company. The imple mentation of lean was undertaken for 15 months, resulting in a reduced workforce and timely delivery of orders. It also generated cash through the liquidation of scraps and non-productive assets. A refreshed culture further led to sustained and improved motivation among staff with a sense of achievement.

The main aim of this study is to examine the interconnections among performance indicators in Small and Medium Scale Enterprises (SMEs) within the mining industries in Kerala, India. A hierarchical model for performance metrics is introduced, starting with the identification of performance indicators through a systematic process. Following this, a comprehensive questionnaire-based survey is conducted within the mining and mineral industries in Kerala to identify the significant indicators specific to the sector. In this context, the Analytic Hierarchy Process (AHP) serves as a valuable multi-criteria decision-making approach for the evaluation of performance indicators. The primary objective of this article is to scrutinize performance indicators that assess the performance of SMEs and provide a comparative rating against their peers. Distinguishing itself from conventional approaches, this study directly engages manufacturers to gauge the relevance of four main factors and twelve sub-factors (performance indicators) through the application of the Analytic Hierarchy Process.

In the era of Industry 4.0, digital human modeling (DHM) may be the key to improving ergonomics related to manual operations in the workplace. Poor workplace ergonomics may lead to reduced work productivity and an increased risk of health problems among employees, resulting in actual losses for enterprises, e.g., sickness absence, employee turnover, and training. DHM technology can help speed up ergonomic analysis and improvement. This paper proposes a methodological framework based on DHM to improve ergonomics in the workplace. Its purpose is to provide practitioners with an easy and detailed approach to ergonomics assessment and improvement procedures. The framework developed two main stages: the workplace Research Stage and the DHM and Simulation Stage, which cover the eight detailed steps of an effective DHM-based ergonomic assessment together. A case study was used to verify and demonstrate the effectiveness of the proposed methodological framework.

The purpose of the work presented here is a comparative analysis of two methods of solving the problem of optimizing the working time and path length of operators for manual harvesting of raspberries over an area of one hectare. An analytical solution is a method of solving mathematical problems based on finding an exact formula that describes a phenomenon or process. A simulation solution is the opposite of a numerical solution, which is based on calculating an approximation using statistical methods. An analytical and simulation approach will be presented to show how to calculate the number of workers needed, the minimum working time and the length of the path taken by raspberry fruit pickers. The results obtained for the two methods are compared.

Engineering plays a significant role in the advancement of medicine. One example of this is endoprostheses, which are prostheses implanted inside the body. Hip joint endoprostheses are commonly implanted nowadays, greatly improving physical fitness and the associated quality of life. However, a potential risk in using such endoprostheses is the possibility of dislocation. In this presented work, systems of forces acting on the limb were subjected to analysis, identifying unstable states that increase the risk of dislocation. Most of the analyses are qualitative, presenting rather than solving the problem. Nevertheless, a quantitative approach was presented for the case of dynamic forces generated during kicking a soccer ball. For this purpose, computer simulation was employed, based on an appropriate mathematical model.

In the logistics center (warehouse or distribution center), customer orders need to be picked up by the pickers. In this research, we examine the order-picking problem with sequencedependent constraints with two decision variables (container start time and product quantity) in a distribution center with a one-directional conveyor. The decision-making is based on the developed two variations of two-step matheuristics. At first, the main order-picking problem is divided into two subproblems. Next, each step of each variant of the subproblem is solved using a mathematical programming-based technique. Both matheuristics were better in 85 of 120 test instances compared to the initial model solved by mathematical programming. Pickers matheuristics were better on average at 46.56%, while Buffers matheuristics were better on average at 46.87%. The proposed matheuristics approach allows distributors to schedule orders in the logistics center fast enough and with fewer resources.

The purpose of the research process was to assess the state of knowledge on the use of Industry 4.0 postulates in the context of Engineer 4.0 and Manager 4.0 competencies in family firms, identify research gaps and outline future research directions. We conducted a systematic literature review of 21 articles from the Scopus database that relate to the topic of Industry 4.0 and Engineer 4.0 and Manager 4.0 in family firms. To identify the state of the art, keyword co-occurrence analysis using VosViewer software was used as an analytical tool. We identified the most influential journals and subject areas. The study allowed us to identify consistent clusters that show a wide variety of topics in the discussion of the mentioned topic. The results showed a wide dispersion of research interests and the lack of a single, in-depth or dominant research area dealing with the phenomenon worldwide. We recommend further research on family businesses and Industry 4.0. In addition, the lack of comparative research on family and non-family businesses should be addressed. Contribution and added value: Our systematic literature review systematizes the existing literature on Industry 4.0 in family firms, isolates key research interests, identifies future research directions and provides important insights for researchers.

In response to the urgent need for sustainable energy, this study addresses a critical challenge in wind turbine optimization. It focuses on developing a nuanced preventive maintenance strategy to minimize costs and mitigate energy losses. Within this framework, our paper introduces a novel approach employing a Monte Carlo simulation to identify the optimal preventive maintenance frequency, striking a balance between cost efficiency and energy loss mitigation. The results show, that grouped maintenance approach, pinpointing an optimal frequency of 93 months. This strategic configuration minimizes costs to $9997 while concurrently maintaining an average energy loss of 32.014 MWh, resulting in a notable 4.29% increase in total energy production. Variability analysis reveals that increasing maintenance frequency reduces cost fluctuations, while energy loss remains relatively stable. These findings elucidate the interplay among preventive maintenance strategies, cost, and reliability in the realm of wind turbine performance optimization

This study employed two primary approaches to determine the optimum structure: the lightweight and sustainable models. The lightweight model considered various factors such as materials, geometry, and dimensions of the brake disc rotor and brake pads. On the other hand, the sustainable model considers the manufacturing process and aims to reduce the carbon footprint. To calculate the optimal lightweight structure, finite element analysis was conducted using two different materials to compare the resulting stresses and determine the most appropriate material. Subsequently, four different models were utilized in finite element analysis to evaluate the displacement and stress and establish the optimum structure. Regarding sustainability, two distinct processes were employed to assess the environmental impact and energy consumption to adopt an eco-friendly approach. This paper investigates the transition from the initial brake disc rotor to a lightweight model, employing finite element analysis, topology optimization, and sustainability considerations. The work is achieved by comparing the cost between conventional and 3D printing processes.

Indonesia is widely known as a country with rich biodiversity. Medicinal plants that thrive in Indonesia are utilized as traditional medicine locally known as “jamu”. One of the islands famous for jamu production is Madura Island. As a well-known jamu producer, Madura Island are facing problems related to jamu production. Procurement of medicinal plants is not well controlled. There are no reports of spices procurement and production. When there is an increase in demand or sale of certain jamu, the stock of jamu is commonly inadequate/insufficient This may result in order cancellation. The solution to this problem is to create a production forecasting information system by using single exponential smoothing. The data used is a weekly report on the number of sales of 3 types of jamu from August to October 2024. Mean Absolute Percentage Error (MAPE) testing using an alpha value of 0.1 to 0.9 resulted in “high” accuracy and the forecasted values were close to the actual data values.

Small and Medium Enterprises SME play a crucial role in the global economy through their contribution in countries economy and creation of employment opportunities, and their success heavily relies on the implementation of efficient manufacturing systems like Lean Production(LP). LP is a continuous improvement philosophy based on various lean activities for improving enterprise lean performance. A fuzzy model that integration Fuzzy Consistency Algorithm (FCA) and Fuzzy Analytical Hierarchy Process (FAHP) was proposed as a comprehensive framework to assess the levels of importance and priority of nineteen SME lean activities that categorized into the related five related lean dimensions. FCA was used to construct the fuzzy pairwise comparison matrix to ensure obtaining consistent experts judgment, whereas FAHP was applied to identify the level of importance and priority of lean activities. Identifying the level of importance of lean activities will be contributed in focuses SME efforts in the improvement process on the most important lean activities to ensure effective resource allocation and foster continuous improvement process and offer a practical tool for enhancing their competitiveness and sustainability. The proposed model was applied in Iraqi SME. The result showed that FCA is an efficient approach to construct a consistent judgment matrix. Efficient manger, Kaizen team, supplier relationship, execution customer suggestions and customer satisfaction job rotation are the most important lean activities with level of importance 58.90%, 21.30%, 49.80%, 38.50%, 41.20% respectively. The proposed model can be used for small or medium size enterprise for various production industries.

Business Process mapping (BP mapping) is important for a company to identify their activities. Previous research suggests several approaches for process identification and BP mapping, which would be easier if the company had already implemented a computer-based information system. The research presented in this paper has the purpose of providing an alternative method for BP mapping especially for the company that does not implement the computer-based information system. A proposed method is using job description documents that the company had to identify elements needed to perform BP mapping which are actor, process, document, and flow of documents. A Natural Language Process (NLP) which is text mining method is used for mining job documents to identify those elements that exist in each job position. To illustrate the applicability of the proposed method, samples of job descriptions of 15 companies are taken. It shows that the proposed method can be applied.

Nowaday, many manufacturing companies are integrating Industry 4.0 technology into their operational processes, particularly those aiming to enhance production operations. However, business decision-makers must remain vigilant about potential risks associated with adopting this technology. These risks include initial financial investments for testing and system installation, managing human resources to operate the new system, and concerns regarding data security. This study proposes designing an Industry 4.0 technology system to augment machining machine operations, leveraging Internet of Things (IoT) devices to facilitate connectivity and data transmission. Additionally, it aims to improve production process monitoring through visual management techniques. The machines under study are semi-automatic and lack operational digitization or expansion capacity. Through research on integrating low-cost Industry 4.0 technology into the production process, this study has achieved an annual reduction in production costs by $9593. Moreover, the defect rate for product length dimensions has plummeted from 54.90% per month to zero defects. The study employs the DMAIC method (Define-Measure-Analysis-Improve-Control) cycle within the Six Sigma methodology to investigate and apply low-cost Industry 4.0 technology to production process enhancement. This combined approach can be customized and applied to various business process improvement models, further enhancing the operation of machining machines originally equipped with Industry 3.0 technology.

This paper presents a model for evaluating production strategies, policies and methods based on fuzzy set theory. To illustrate the application of a model, the longitudinal case study was carried out in the sector of automotive components and parts production in Serbia. Within the automotive supplier industry, analysis is concentrated on the Cooper Standard company, one of the world’s most prominent component suppliers. The study was conducted with the management team of the Cooper Standard branch in Serbia. Triangular fuzzy numbers are employed to effectively evaluate the critical areas of production management and overall competitiveness over time. The findings of the empirical survey confirmed the usability and usefulness of the proposed approach. Also, the longitudinal character of this case study provided an opportunity to follow the patterns of change over a period of 5 years (2019–2024).

his study explores the impact of augmented reality (AR) on worker performance in manufacturing contexts through an analysis of case studies extant in the literature. Two specific analyses were conducted to assess the impacts of AR technologies on worker performance in terms of objective and subjective metrics, and in terms of their age, experience with the task and experience with the AR device. Regarding objective metrics, the results showed that the task completion time was reduced for some AR devices (projectors, monitors, tablets, smartphones), whereas the use of the head-mounted display (HMD) increased task-completion time; moreover, the error rate was reduced with any AR device compared with traditional methods. Regarding subjective metrics, the analysis underlined that operator perceived a lower workload with the HMD or the monitor compared with traditional methods. The age of operators did not influence performance, while the operators’ experience allowed for the improvement of human performance.

The fourth industrial revolution has broadly transformed the manufacturing system. However, this transformation is somewhat lacking in traditional or manual production systems due to the absence of IT infrastructure. Such traditional industries need to have the advantage of real-time control and monitoring. This study has developed economic assembly planning, scheduling, and control for a traditional assembly system. We used the concept of the configurable virtual workstation as the digitalization framework. Then, we employed the decentralized scheduling concept to reduce the computational effort in scheduling the complex product. The implementation result showed that scheduling and planning have transformed the traditional assembly process into intelligent scheduling and control with low digitalization effort

The objective of this research is to minimize product defects based on labor performance and prove the hypothesis on how labor performance affects the quality of a product through a scientific calculation using Overall Labor Effectiveness (OLE). The primary data is obtained by interviewing the supervisor and labor directly. For secondary data is obtained from the company, such as labor working time, machine scheduled downtime, total production, and defective products. The approach to extract the data is using OLE and the continued regression method. Furthermore, it proceeds to Six Sigma using the DMAIC approach since the results show a significant correlation. The result from Failure Mode and Effects Analysis (FMEA) shows four of six potential failures caused by product defects are coming from labor. To prevent failure mode, it is recommended to have the regular machine checked by labor, check the temperature of the machine, and provide Standard Operating Procedures.

Currently, we live in a culture of being overly busy, but this does not translate into efficiency, speed of implementation of the actions taken. Enterprises are constantly looking for methods and tools to make them more efficient. The most popular method of production management is Lean Manufacturing, less known is Theory of Constraints. This work is a continuation of the research on the comparison of these methods with apply a computer simulation, which the analyzed production process in the selected enterprise, after 24 hours and week. An attempt was made to simplify the comparison of the methods based on the obtained simulation in terms of costs. In analyzed case, more advantageous solution is to use the DBR method. To produce various orders that do not require 100% production on the bottleneck position, the use of Kanban is a frequent practice as it provides greater flexibility in order execution.

Quality profiling seeks to know the quality characteristics of products and processes to improve customer satisfaction and business competitiveness. It is required to develop new techniques and tools that upgrade and complement the traditional analysis of process variables. This article proposes a new methodology to model quality control of the process and product quality characteristics by applying optimization and simulation tools. The application in the production process of carbonated beverages allowed us to identify the most influential variables on the gas content and the degrees Brix of beverage.

Organisations have to take into account rapid, non-linear changes in their environment that build pressure on the company‘s development strategy. Therefore, one of the key challenges and paradoxes is to how maintain mutual coherence between different areas of the organisation and simultaneously leverage being ambidextrous so as to continue with exploration and exploitation activities. The main goal of this paper is to present research results on the relation between strategic coherence and company ambidexterity.
Strategic coherence is a proprietary concept allowing for measurement of the balance between the vertical and horizontal adjustment of an organisation. Vertical adjustment is the relation between strategy and the elements of the business model measured by: 1) the cascading of goals, 2) feedback on matching elements of the business model according to strategy, and 3) control over financial results and strategy implementation. Horizontal adjustment refers to matching the business model components measured by: 1) creating value, 2) capturing value, and 3) creating a synergy effect) Meanwhile, ambidexterity is determined by four areas: 1) company goals, 2) products, 3) market and 4) competitive advantage for both exploration and exploitation activities. The research survey was conducted with the use of the CATI method. Altogether, 400 medium-sized and large Polish companies were included in the study. To calculate the dependencies, the Pearson correlation coefficient was applied. The companies studied achieved similar results in terms of strategic coherence dimensions, as the vertical adjustment was 6.47, and the horizontal was 6.29 on a scale of 1–10. Meanwhile, in terms of ambidexterity, the companies achieved a moderate level, with the average value for exploration being 4.26, and that for exploitation 4.51 on a scale from 1 to 7. Based on correlation analysis, the relation between both variables has the shape of an inverted “U” with the most favourable point for ambidexterity at the “high strategic coherence” level. This study is a comprehensive guide for practitioners, and presents development guidelines for companies. The value of this research is an empirically validated framework that describes relations based on a dynamic balance between strategic coherence and two types of adjustment in the area of regulation – vertical and horizontal, as well as ambidexterity with two types of activity in the area of operations: exploration and exploitation. This study is unique and explores uncharted areas of strategic management.

The article explores megatrends in management, related to the transition to digital technologies in all spheres of the economy and production in the COVID-19 pandemic. The main contribution to the analysis of the current state of digitalization HR in business. The possibilities of a set of processes and methods of interaction with information in the formation of a strategy of people’s management, are investigated. This is achieved through the use of integrated mobile applications and the automation of HR processes. From the results, the methodology for determining the severity of competences, indicators of behavior are proposed, the strengths and weaknesses of the company’s staff management system in the COVID-19 conditions are taken into account. The practical usability of work is due to the proposed competency-based approach, which makes it possible to increase the efficiency of personnel selection, taking into account key macro-competencies that find an applied form through appropriate behavioral indicators.

Agile Project Management is a topic that has become popular both in business and academia, since the publication of the Agile Manifesto – a historic landmark in this subject. In the next 20 years, there was a relevant scientific production that must be analyzed to provoke reflection about the knowledge built up in this period. In this sense, this study aims to analyze the relevant scientific literature on Agile Project Management through a systematic review and a bibliometric analysis of articles published in scientific journals with Digital Object Identifier, in English, from the Web of Science and Scopus databases, from 2001 to 2021. The research results enable us to gain insights into the characteristics of this knowledge domain, regarding its volume and evolutionary trend, main contributors (i.e. scientific journals, authors, and their affiliations), main studies, methods used, and its central thematic axes.