To increase their competitive advantage in turbulent marketplaces, contemporary manufacturers must show determination in seeking ways to: fulfill buyer orders with quality merchandise; meet deadlines; handle unexpected production disruptions; and lower the total relevant expense. To tackle the abovementioned challenges, this study explores an economic manufacturing quantity (EMQ) model with machine failure, overtime, and rework/disposal of nonconforming items; the goal is to find the best fabrication uptime that minimizes total relevant expenses. Specifically, we consider a production unit with overtime capacity as an operational feature that is linked to higher unit and setup costs. Further, its EMQ-based process is subject to random nonconforming items and failure rates. Extra screening separates the reworkable nonconforming items from scrap, and the rework is executed at the end of each cycle of regular fabrication. The failures follow a Poisson distribution, and a machine repair task starts as soon as a failure occurs; the fabrication of the lot that was interrupted resumes after the repair has been carried out. A decision model is built to capture the characteristics of the problem. Mathematical and optimization processes help in determining the optimal fabrication uptime. A numerical example not only illustrates the applicability of the research outcomes, but also reveals a diverse set of information about the individual or joint influences of deviations in mean-time-to-failure, overtime factors, and rework/disposal ratios linked to nonconforming rates related to the optimal replenishment uptime, total operating expenses, and various cost contributors; this facilitates better decision making.
Industry 4.0 (I4) as a concept offers powerful opportunities for many businesses. The set of Industry 4.0 technologies is still discussed, and boundaries are not perfectly clear. However, implementation of Industry 4.0 concept becomes strategic principle, and necessary condition for succeeding on turbulent markets. Radio Frequency Identification (RFID) was used before I4 emerged. However, it should be treated as its important part and even enabler. The question arises how adoption of RFID was impacted by I4 paradigm. Therefore, to answer this question a set of technology management tools was selected and applied to forecast RFID potential development in forthcoming years. Moreover, case studies were conducted for technology management tools and their applications for RFID for qualitative discussion of its relevance. It aimed to prove that existing toolset should be applied for modern technologies related to I4. Tools were proven to be necessary and successful. However, some specific challenges were observed and discussed.
The presence of the spare parts stock is a necessity to ensure the continuity of services. The supply of spare parts is a special case of the global supply chain. The main objective of our research is to propose a global spare parts management approach which allows decision makers to determine the essential points in stock management. Thus, it is important for the stock manager to evaluate the system considered from time to time based on performance indicators. Some of these indicators are presented in the form of a dashboard. The presentation of this chapter chronologically traces the progress of our research work. In the first part, we present the work related to the forecast of spare parts needs through parametric and statistical methods as well as a Bayesian modelling of demand forecasting. To measure the appreciation of the supply of spare parts inventory, the second part focuses on work related to the evaluation of the performance of the spare parts system. Thus, we concretize the link between the management of spare parts and maintenance in the third part, more precisely, in the performance evaluation of the joint -management of spare parts and maintenance, in order to visualize the influence of parameters on the system. In the last section of this chapter, we will present the metaheuristic methods and their use in the management of spare parts and maintenance and make an analysis on work done in the literature.
So far, numerous studies have been published on the selection of appropriate maintenance tactics based on some factors affecting them such as time, cost, and risk. This paper aims to develop the TRIZ contradiction matrix by explaining the dimensions and components of each of the following Reactive maintenance tactics. The related findings of previous studies were analyzed by adopting “Rousseau and Sandoski” seven-step method to identify and extract the relationships between TRIZ principles and Reactive maintenance tactics. Thereafter, 5 Reactive maintenance tactics were replaced TRIZ’s 40 principles in the TRIZ contradiction matrix. Finally, the ANP method were used to extract and prioritize the appropriate Reactive maintenance tactics. The proposed matrix in this research was used in the desalination section of one of the oil companies to select on the appropriate Reactive maintenance tactics. The results of this research is useful for managers and maintenance specialists of units in making decisions to provide appropriate Reactive maintenance tactics for the desired equipment.
Industry 4.0 promises to make manufacturing processes more efficient using modern technologies like cyber-physical systems, internet of things, cloud computing and big data analytics. Lean Management (LM) is one of the most widely applied business strategies in recent decades. Thus, implementing Industry 4.0 mostly means integrating technologies in companies that already operate according to LM. However, due to the novelty of the topic, research on how LM and Industry 4.0 can be integrated is still under development. This paper explores the synergic relationship between these two domains by identifying six examples of real cases that address LM-Industry 4.0 integration in the extant literature. The goal is to make explicit the best practices that are being implemented by six distinct industrial sectors
Major manufactures are moving towards a sustainability goal. This paper introduces the results of collaboration with the leading company in the packaging and advertising industry in Germany and Poland. The problem addresses the manufacturing planning problem in terms of minimizing the total cost of production. The challenge was to bring a new production planning method into cardboard manufacturing and paper processing which minimizes waste, improves the return of expenses, and automates daily processes heavily dependent on the production planners’ experience. The authors developed a module that minimizes the total cost, which reduces the overproduction and is used by the company’s manufacturing planning team. The proposed approach incorporates planning allowances rules to compromise the manufacturing requirements and production cost minimization.
The industrial revolution taking place since the 18th century has brought the global economies to the stage of mass production, mass industrialization and spreading ideas connected with its efficiency. The most famous of its kind is Fordism and its modern variations called PostFordism or Neo-Fordism. We can still see traditional way of producing things in some parts of the world, and the leading economies are using Ford’s ideas or the modifications of the Ford’s concepts. But there is a question about the place of these models in the modern economy, especially because mass-production causes mass-waste and modern societies has woken up to the reality of the global pollution, climate change or just the simple fact that the amount of the raw materials is limited. The social mood is slowly changing so there should be a change to the way we produce and consume things as well. There is a question: can we proceed within existing models or should we think outside the box so we can invent more suitable way of looking at efficiency and effectiveness. The objective of this paper is to contribute to the discussion about the future of how are we going to produce things. It is based on the literature review considering Fordism and its variations, Product Life Cycle facing issues like pollution, massive waste and changes in modern economy, as well as on the case study of implementing waste reduction activities in the product’ design phase in the industrial plant based in one of the EU countries – Poland.
As the corporate culture and re/setting of employer – employee relations is crucial due to changes in workplace due to impact of COVID-19, this article aims to identify types of organizational culture, and to find impact on the implementation of HR activities and employer branding, including classification of organizations by their defined strategies. A model of organizational culture, including its systematic relationships, is proposed and tested using a sample of 402 organizations across sectors operating in the Czech Republic as a characteristic economy in Central Eastern European region. This model includes different dimensions of internal brand management and manifestations of organizational culture. Data are analyzed using bivariate and multivariate statistics. Identification of a suitable type of organizational culture leads towards successful employer branding and work engagement; brand identification and communication directly raise positive perception of organizational culture. Three major areas of use of organizational culture and branding have been identified: re-setting of personnel processes depending on the change of organization’s size, on the decline in labor productivity and on organizational mergers, changes in scope of business and in market position. The results suggest that orientation on employee engagement is a better predictor of (positive) organizational culture than increase in productivity. Furthermore, the results explain supportive roles of organizational culture towards customers and employees. The results extend theory by empirical analysis of organizational culture and internal brand management from the employers’ perspective.
Commercialization processes are modeled and analyzed from the point of view of the implementation of activities under particular stages. These issues are the subject of many studies and analyzes, which is why the extensive literature is available on this subject. Technology valuation at various stages of the commercialization process is a separate issue. Such valuation is prepared in most cases by consulting companies for determining the price in the buying and selling processes. These valuations use known methods also used in other cases, e.g., real estate valuation. The work carried out presents the author’s concept of the commercialization process model, taking into account the costs and value of the technology at various stages of the product life cycle. The model uses a stochastic approach to determine future revenues and costs, which allows estimating the value of the technology by or in determining the probability of assessment validity. The proposed stochastic approach greatly increases the chances of using the presented solutions in practical activities related to technology valuation for the purposes of purchase and sale transactions.
The market of consumer goods requires nowadays quick response to customer needs. As a consequence, this is transferred to the time restrictions that the semi-finished product manufacturer must meet. Therefore the cost of manufacturing cannot determine how production processes are designed, and the main evaluation function of manufacturing processes is the response time to customers’ orders. One of the ideas for implementing this idea is the QRM (Quick Response Manufacturing) production organization system. The purpose of the research undertaken by the authors was to develop an innovative solution in the field of production structure, allowing for the implementation of the QRM concept in a Contract Manufacturer, which realizes its tasks according to engineering-to-order (ETO) system in conditions defined as High Mix, Low Volume, High Complexity. The object of the research was to select appropriate methods for grouping products assuming that certain operations will be carried out in traditional but well-organized technological and/or linear cells. The research was carried out in one of the largest producers of sheet metal components in Europe. Pre-completed groupings for data obtained from the company had indicated that – among the classical methods – the best results had been given by the following methods: King’s Algorithm (otherwise called: Binary Ordering, Rank Order Clustering), k-means, and Kohonen’s neural networks. The results of the tests and preliminary simulations based on the data from the company proved that the implementation of the QRM concept does not have to be associated with the absolute formation of multi-purpose cells. It turned out that the effect of reducing the response time to customer needs can be obtained by using hybrid structures that combine solutions characteristic of cellular systems with traditional systems such as a technological, linear, or mixed structure. However, this requires the application of technological solutions with the highest level of organization.
Artificial neural network (ANN), a Computational tool that is frequently applied in the modeling and simulation of manufacturing processes. The emerging forming technique of sheet metal which is typically called single point incremental forming (SPIF) comes into the map and the research interest towards its technological parameters. The surface quality of the end product is a major issue in SPIF, which is more critical with the hard metals. The part of the brass metal is demanded in many industrial uses because of its high load-carrying capacity and its wear resistance property. Considering the industrial interest and demand of the brass metal products, the present study is done with the SPIF experiment on calamine brass Cu67Zn33 followed by an ANN analysis for predicting the absolute surface roughness. The modeling result shows a close agreement with the measured data. The minimum and maximum errors are found in experiment 3 and experiment 7 respectively. The error of predicted roughness is found in the range of –30.87 to 20.23 and the overall coefficient of performance of ANN modeling is 0.947 which is quite acceptable.
The aim of the article is to present an exemplary system for recording and analyzing quality costs and to demonstrate that it is helpful in planning and assessing the effectiveness of continuous improvement processes at the operational and strategic level. Various approaches to defining quality costs are described, followed by indicators for assessing effectiveness and tools to collect data on the values of individual groups of quality costs and compare them with financial indicators. The practical part presents a case study on the quality cost accounting system in a medical company and the possibility of using quality cost accounting to plan and evaluate continuous improvement processes and make managerial decisions.
The aim of our research is to gain understanding about material flow related information sharing in the circular economy value network in the form of industrial symbiosis. We need this understanding for facilitating new industrial symbiosis relationships and to support the optimization of operations. Circular economy has been promoted by politics and regulation by EU. In Finland, new circular economy strategy raises the facilitation of industrial symbiosis and data utilization as the key actions to improve sustainability and green growth. Companies stated that the practical problem is to get information on material availability. Digitalization is expected to boost material flows in circular economy by data, but what are the real challenges with circular material flows and what is the willingness of companies to develop co-operation? This paper seeks understanding on how Industry 4.0 is expected to improve the efficiency of waste or by-product flows and what are the expectations of companies. The research question is: How Industry 4.0 technologies and solutions can fix the gaps and discontinuities in the Industrial Symbiosis information flow? This research is conducted as a qualitative case study research with three cases, three types of material and eight companies. Interview data were collected in Finland between January and March 2021. Companies we interviewed mentioned use-cases for sensors and analytics to optimize the material flow but stated the investment cost compared to the value of information. To achieve sustainable circular material flows, the development needs to be done in the bigger picture, for the chain or network of actors, and the motivation and the added value must be found for each of them.
In digital revolution, the appropriate IT infrastructure, technological knowledge are essential for the success of companies, where the success of the digital transformation depends on digital maturity. The aim of the study is to define the digital maturity, theoretical foundation of the digital maturity model and present a framework for small and medium-sized enterprises (SMEs) understanding where they are in digitalisation (how advanced their digital resource system and digital approach) to respond faster and efficiently to environmental changes. The model construction is based on theory of dynamic capabilities, graduation models, and SMEs management challenges. The model is a dynamic model to support management in strategic, digital and organizational developments, which is divided into IT and organizational dimensions, including 6 components and 28 subcomponents. The ultimate goal of the study is to determine the component weights to create a neurofuzzy model.
Technological progress is the driving force behind industrial development. It is a multidimensional and multi-level phenomenon. In this article we focus on its three manifestations: information and communication technologies (ICT), Industry 4.0 and agile manufacturing. The aim of this article is to analyse the relationship between these constructs as they are undoubtedly interrelated. ICT plays a key role, but it is not a goal itself. They are a prerequisite for the implementation of Industry 4.0, but together with it they serve to achieve agility by the manufacturing system and, as a result, achieve a competitive advantage by companies operating in turbulent and unpredictable environment. The literature findings in this paper are part of a broader study conducted on the impact of ICT on agility of SMEs operating in India. Therefore, we include also subsections showing the level of this relationship in Indian SMEs.
Enterprise innovation is currently becoming a recognized factor of the competitiveness, survival, and development of companies in the market economy. Managers still need recommendations on ways of stimulating the growth of innovation in their companies. The objective of this paper is to identify the strategic factors of enterprise innovativeness in the area of technology, defined as the most important internal factors positively impacting the innovativeness of enterprises in a strategic perspective. Empirical studies were conducted using the Computer-Assisted Web Interview (CAWI) method on a purposive sample of N = 180 small and medium-sized innovative industrial processing enterprises in Poland. Data analysis was performed using Exploratory Factor Analysis within the Confirmatory Factor Analysis framework (E-CFA) and Structural Equation Modeling (SEM). Empirical research shows that the strategic factor of enterprise innovativeness in the area of technology is technological activity. A technologically active company should (1) possess a modern machinery stock, (2) conduct systematic technological audits, and (3) maintain close technical cooperation with the suppliers of raw materials, consumables, and intermediates. The implementation of the indicated recommendations by managers should lead to increased innovativeness of small and medium-sized industrial companies. The author recommends the use of the presented research procedure and data analysis methods in further studies.
In this article conclusions from nearly 10 years of collaboration with Polish and German Engineer-to-Order (ETO) small and medium-sized enterprises (SMEs) from mechanical sector was presented. Research objective was to highlight common organizational problems they are dealing with, which prevent them from transition to Mass Customizers. As a result, a concept of 5 foundations for robust process design was proposed: procedures, product selection, machining philosophy, planning and storage, cross-functional teams. More practical solutions from this field have to be published to fill the research gap.
Wire electrical discharge machining (WEDM) is a non-conventional material-removal process where a continuously travelling electrically conductive wire is used as an electrode to erode material from a workpiece. To explore its fullest machining potential, there is always a requirement to examine the effects of its varied input parameters on the responses and resolve the best parametric setting. This paper proposes parametric analysis of a WEDM process by applying non-parametric decision tree algorithm, based on a past experimental dataset. Two decision tree-based classification methods, i.e. classification and regression tree (CART) and Chi-squared automatic interaction detection (CHAID) are considered here as the data mining tools to examine the influences of six WEDM process parameters on four responses, and identify the most preferred parametric mix to help in achieving the desired response values. The developed decision trees recognize pulse-on time as the most indicative WEDM process parameter impacting almost all the responses. Furthermore, a comparative analysis on the classification performance of CART and CHAID algorithms demonstrates the superiority of CART with higher overall classification accuracy and lower prediction risk.
The present paper describes a methodological framework developed to select a multi-label dataset transformation method in the context of supervised machine learning techniques. We explore the rectangular 2D strip-packing problem (2D-SPP), widely applied in industrial processes to cut sheet metals and paper rolls, where high-quality solutions can be found for more than one improvement heuristic, generating instances with multi-label behavior. To obtain single-label datasets, a total of five multi-label transformation methods are explored. 1000 instances were generated to represent different 2D-SPP variations found in real-world applications, labels for each instance represented by improvement heuristics were calculated, along with 19 predictors provided by problem characteristics. Finally, classification models were fitted to verify the accuracy of each multi-label transformation method. For the 2D-SPP, the single-label obtained using the exclusion method fit more accurate classification models compared to the other four multi-label transformation methods adopted.
Occupational risk is closely related to work environment. For the same positions, but in different working conditions threats and level of risk can be different. For this also estimating the degree of damage hazard the largest possible should be adopted effects. However, when estimating probability occurrence of threats should include, among others: working conditions, events from the past, or possible employee behavior (in particular those that may be the cause of an accident at work). The source of the above information may be data from statistics or observations of work stations. The article presents the assessment of occupational risk at the position of the laser cutter operator, which was carried out using the Job Safety Analysis (JSA) method. According to this method, occupational risk is determined on the basis of two parameters, i.e.: consequences of C and probability of consequences P. In turn, the probability of consequences is the sum of three factors: frequency of hazard F, probability of event O and avoidability or damage limitation A.
This study investigates (1) the effect of quality information on quality performance through process control and (2) the moderating role of shop floor leadership on the relationship between quality information and quality performance in the context of manufacturing plants on a global basis. The moderated mediation analysis with a bootstrapping approach was employed to analyse data for hypotheses testing. The data is from the fourth-round dataset of the High- Performance Manufacturing Project, collected from manufacturing plants worldwide. The results indicate that (1) quality information is positively associated with quality performance through process control, and (2) shop floor leadership (i.e., supervisory interaction facilitation) positively moderates the indirect effect of quality information on quality performance; that is, the shop floor leadership practice strengthens the effect of quality information on quality performance through process control. This study also has a practical implication for top managers who should consider the vital role of leadership practices adopted by shop floor supervisors in implementing total quality management practices and should raise awareness that leadership practices are not only for the ‘C-suite’ but also for shop floor supervisors.
Management processes in an organization involve decision-making based on many criteria (MCDM), and in this process ranking of variables plays a vital role. This paper presents the analysis of key business issues of an Indian automotive organization using an efficient interpretive ranking (eIRP) approach. This paper integrates the Situation-Actor-Process (SAP) and Learning-Action-Performance (LAP) framework of the organization with eIRP. It evaluates the ranking of actions to be carried out in an organization with respect to performance parameters. The study highlights the area where the organization should focus on achieving desired business excellence. From the analysis, it is revealed that the top-ranked suggested action for the organization is the adoption of energy policy as a core business policy followed by technology management, maintenance management, and the use of information technology for cost management. This case study is one of the few that uses the SAP-LAP framework for ranking the actors and actions of the organization using the eIRP approach, to make MCDM an easy task.
Digital twin (DT) is a solution for presenting reality in a virtual world. DTs have been discussed in the literature only recently. The aim of this work is to review and analyse literature connected to DTs. Under a systematic literature review the authors searched databases for the information how DTs can support organization operations and how they can support sustainability of companies. A literature review was performed according to a developed research methodology, which covers research questions and keywords identification, selection criteria and results analysis. Databases, such as Web of Science, Scopus and Science Direct, were searched. The titles, abstracts and keywords were searched for works related to digital twins, sustainable development and manufacturing processes. Moreover, the search was focused on real-time monitoring, data, decision-making etc. The keywords used in the searching process are specified in the methodology. Afterwards, quantitate and qualitative analysis were performed taking into account number of publication, year of publications, type of publication, based on keywords and available information concerning the papers. Deeper analysis was performed on available full texts of the papers. The main goal of this paper was to assess how much the specified problem is discussed in literature in the context of production organizations and real-time and what kind of topics are present in publications to indicate future research needs.
In mid-1992, Japanese consultant Yamada Hitoshi was tasked with modifying the production systems of Japanese companies as the existing configurations at manufacturing plants no longer satisfied unstable demands. He made improvements to the overall production system by dividing the long assembly lines into several short ones called cells or seru. Although of the advantages, it is still unclear about how to manage this new production system, and what variables really promoted the desired benefits. We identify in total 39 articles from 2004– 2020 about the progress of the seru production system, and we observe some possibilities to improve the effectiveness of this type of the production system. The first is the possibility of manufacturing the product in flexible sequence, in which the operations are independent among them. We show through the developed example that the makespan may be different. We noted when converting the in-line production system to one pure seru, the makespan tend to increase. Nevertheless, when analyzing the effectiveness of serus working concomitantly considering splitting the same lot, makespan and the cost may be reduced. And finally, when converting to one of pure serus, the performance may be similar to that obtained when serus working concomitantly.
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