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.
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.
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.
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.
The article is devoted to the development of a multicomponent adaptive strategy for managing Russian high-tech enterprises in modern crisis conditions. Adaptability and flexibility are considered as the most important indicators of the efficiency of structures, their ability to ensure sustainable operation and effective innovative development of high-tech enterprises. A significant place in the article is devoted to possible approaches and methods of adaptive management of the enterprise in crisis, with the help of which changes in the internal and external environment are monitored, which can be expected and random, make current operational decisions that contribute to the achievement of pre-set goals based on correction of certain tasks. The questions about the quality of adaptation, adaptive characteristics of the structure and their consistency with the level and quality of adaptation of other elements of the enterprise, conjugation of adaptability and flexibility and pace of changes are considered. A number of modern techniques related to the development of strategies for the development of high-tech enterprises in crisis conditions are analyzed. The necessity of conducting a comprehensive accounting of the crisis as the main factor associated with the uncertainty of the external environment at the stage of strategic analysis is substantiated. There is an option, in which it is possible to include the crisis and its main characteristics into the strategic three competence model of the enterprise, as an additional controlled parameter. There is a general specificity of the formation of the strategy of a high-tech enterprise in conditions of risk and uncertainty.
This paper is the first to optimize the friction stir welding (FSW) process considering the Clamp Pitch (mm) and Clamping Torque effect using the Various combinations of parameters were constructed using factorial design and responses, resulting in a comprehensive factorial analysis. Conspicuous changes in the tensile strength, yield strength, hardness, and power profile were observed for all amalgamations of parameters. Significant parameters of the FSW process have been considered in many optimization studies, however, the effect of the Clamp Pitch (mm) and Clamping Torque (Nm) has been never studied. Three levels of three parameters were used in the experiments: Clamp Pitch, tool rotational speed and Clamping Torque. The full factorial analysis was performed, was applied as an approach for selecting the values of the Significant factors of the parameters. For each result the three key parameters were important with p-values of less than 0.05, suggesting their significance in the phase of FSW. Mathematical models built with high R-sq. and least percentage error were adequate for the investigated responses. The findings were gained by important parameter values factors of 30 mm, 1800 rpm and 70 Nm for the take into consideration parameter range for the Clamp Pitch, rotational speed and Clamping Torque respectively.
Warehouse and inventory management is a recurring issue in many of the different supply chains in diverse industries, where the constant changes in the markets have a direct impact on the management of warehouses and inventories, either generating over-stocks or shortages. This paper presents a case study on warehouse and inventory management control. The company under study was having problems in this area, where over-stocks were generated frequently, leading to various incidents, such as having to store finished and packaged product in unsuitable places, with the associated risk of deterioration. To deal with this problem, control tools based on the KPI (Key Performance Indicator) concept were developed. To this end, the corresponding problem and the information management process within the Supply Chain department had to be analyzed. In this case, it was observed that the databases were not synchronized, therefore strategies were proposed to systematize the collection and updating of data. In addition, to summarize the information, we proceeded to the implementation of an interactive form that facilitates the visualization and interpretation of the evolution of the process, and to be able to apply an efficient control on it, and thus to propose corrective actions supported by evidence.
Supply chain management emerged as the ultimate management strategy to ensure the competitive advantages of companies in their markets. Suppliers are considered as inevitable sources of external risks in modern supply chains. In this respect, resonance is essential for the ability to adapt in resonance to disturbances and to restore in choosing suppliers. As suppliers of critical resources are vulnerable, choosing better suppliers to create resilience, and thereby reducing the risks in the supply chain as a whole. In recent years, emphasis has been placed on supply chain resilience and resilient suppliers, but few studies have been conducted on the evaluation and selection of resilient suppliers with multi-criteria decision making models. The main purposes of this study are a broad review of the literature on the resilient factor, factorization, efficiency of key factors in the reliance of suppliers and the ranking of resilient suppliers using the combined approach of SWARA and WASPAS. For this purpose, after a comprehensive review of Literature interview with the experts of petrochemical upstream industry, six key factors and overall resilience of suppliers were identified in eighteen factors. Then the weight of the dimensions was determined by using the SWARA method. The output of the method showed that supplier accountability and key performance factors were the most important factors in assessing the resilience of suppliers. Using the supporting method, five resilient suppliers were evaluated based on six dimensions and the final ranking of suppliers was determined. With this ranking, the industry will be a major step towards improving supply chain and increasing suppliers’ resilience to address disruptions and risks, improve supply and achieve competitive advantage and satisfy the consumers’ needs.
Unrelated Parallel Machines Scheduling Problem (U-PMSP) is a category of discrete optimization problems in which various manufacturing jobs are assigned to identical parallel machines at particular times. In this paper, a specific production scheduling task the U-PMSP with Machine and Job Dependent Setup Times, Availability Constraint, Time Windows and Maintenance Times is introduced. Machines with different capacity limits and maintenance times are available to perform the tasks. After that our problem, the U-PMSP with Machine and Job Dependent Setup Times, Availability Constraints, Time Windows and Maintenance Times is detailed. After that, the applied optimization algorithm and their operators are introduced. The proposed algorithm is the genetic algorithm (GA), and proposed operators are the order crossover, partially matched crossover, cycle crossover and the 2-opt as a mutation operator. Then we prove the efficiency of our algorithm with test results. We also prove the efficiency of the algorithm on our own data set and benchmark data set. The authors conclude that this GA is effective for solving high complexity parallel machine problems.
Small and medium-sized enterprises (SMEs) are facing barriers to grow due to the lack of structured procedures for upgrading and allocating the limited resources. To overcome these drawbacks and to improve business capabilities, a structured framework to conduct a comprehensive diagnostic and upgrading study is presented in this paper. The proposed framework involves four phases. First, the external and internal strategic factors, which can affect the enterprises’ performance are evaluated using strategic planning and assessment tools. Second, key upgrade performance indicators are developed and evaluated using multi-attribute rating techniques to guide, evaluate, and track progress of upgrading process. Third, a set of upgrade strategies are generated and evaluated using resource allocation model. Finally, a periodic re-evaluation plan is introduced to monitor the implementation progress. The developed framework for performance evaluation and upgrading is suitable to be used as a structured know-how procedure in manufacturing enterprises and can support entrepreneurs in their strategic decisions. To validate the proposed framework, a data set was collected from a local housecore company. As a result, one package of the efficient frontier strategies that represents the best use of resources was proposed for implementation.
Nowadays, the main challenge in maintenance is to establish a dynamic maintenance strategy to significantly track and improve the performance measures of multi-state systems in terms of production, quality, security and even the environment. This paper presents a quantitative approach based on Dynamic Bayesian Network (DBN) to model and evaluate the maintenance of multi-state system and their functional dependencies. According to transition relationships between the system states modeled by the Markov process, a DBN model is established. The objective is to evaluate the reliability and the availability of the system with taking into account the impact of maintenance strategies (perfect repair and imperfect repair). Using the proposed approach, the dynamic probabilities of system states can be determined and the subsystems contributing to system failure can also be identified. A practical application is demonstrated by a case study of a blower system. Through the result of the diagnostic inference, to improve the performances of the blower, the critical components C, F, W, and P should be given more attention. The results indicate also that the perfect repair strategy can improve significantly the performances of the blower, while the imperfect repair strategy cannot degrade the performances in comparison to the perfect repair strategy. These results show the effectiveness of this approach in the context of a predictive evaluation process and in providing the opportunity to evaluate the impact of the choices made on the future measurement of systems performances. Finally, through diagnostic analysis, intervention management and maintenance planning are managed efficiently and optimally.
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.
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.
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.
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.
en
pl
