Medium-sized Manufacturing Companies Research Articles

Industrial multi-resource flexible job shop scheduling with partially necessary resources

This paper is dedicated to the study of industrial extensions of the flexible job shop scheduling problem with multiple resources in order to propose an alternative to expensive optimization software for small to medium-sized manufacturing companies. In this context, we propose a generic model able to tackle some constraints often found in industrial scheduling problems. This model tackles partially necessary resources by decomposing operations into stages. Instances are solved by a simulated annealing metaheuristic which is further improved using efficient conditions to filter non-interesting solutions. We compare our approach to a constraint programming model using a commercial solver. Extensive experiments and statistical analysis show that our method is competitive and of practical use in the industrial context.

DX프로세스 환경에서의 중소제조기업 보안영역 수립과 보안 가이드라인에 대한 연구

As digital transformation (DX) develops, various security threats occur, mainly in the manufacturing industry. This study considers the characteristics of small and medium-sized manufacturing companies in the DX environment. Moreover, the security threats to small and medium-sized manufacturing companies are derived, security areas are established from technical and management perspectives, and minimal guidelines for each area are proposed. Based on these results, small and medium-sized manufacturing companies can establish security policies that are tailored to the size of the company, assets, importance of work, and business areas that require digital transformation.

Enhancing Green Process Innovation Performance: The Role of Regenerative Unlearning and Knowledge Base Management

Spanish manufacturing companies are urged to adopt greener practices to mitigate their environmental footprint. However, they often lack the knowledge to do so. Following a knowledge-based approach, this study analyzes the role of strategic knowledge management in enhancing organizational green performance. It introduces the concept of regenerative unlearning, defining it as the result of an organizational change that has consequences at the organizational level. Specifically, it tests the direct influence of regenerative unlearning on green process innovation performance and its indirect influence through knowledge breadth and depth. By analyzing 310 Spanish medium-sized manufacturing companies, results show that updating and managing the knowledge base positively impacts the company's green process innovation performance. This implies that leveraging regenerative unlearning as part of companies’ knowledge management strategy is part of the solution to achieving ecological efficiency in the manufacturing industry. Finally, actionable recommendations for industry leaders to improve their green performance are provided.

DESIGN OF MANUFACTURING MANAGEMENT SYSTEM: PRODUCT SALES MANAGEMENT SYSTEM

The advent of Industry 4.0 has fuelled the demand for Manufacturing Management Systems (MMS) in the manufacturing industry. This article presents the design and development of a comprehensive Product Sales Management System (PSMS) tailored for small and medium-sized manufacturing companies, focusing on the dairy product industry. Employing the Rapid Application Development (RAD) approach, the development process prioritised user-friendly interfaces and rapid prototyping. Through meticulous requirements gathering, key features were identified, including product information management, customer information management, sales order management, report generation, product advertisement management, and an analytic dashboard. Unified Modeling Language (UML) diagrams, such as use case, activity, and class diagrams, were utilised to visualise the system's functionalities and ensure alignment with requirements. Iterative development and user feedback enhanced the system's usability, resulting in a user-friendly interface for streamlined product sales handling. The proposed PSMS offers efficient management, enhanced communication, and revenue generation for manufacturing companies and tiny and medium-sized enterprises. Furthermore, the study contributes to an understanding of the system requirements and user interface of a PSMS, providing a valuable reference model for developers and researchers in the manufacturing industry. The proposed PSMS represents a significant step towards efficient product sales management, streamlining operations, and boosting manufacturers' profitability. In future work, the PSMS's user interface will be optimised for better mobile responsiveness, and its functionality will be extended to support collaborative sales management and provide manufacturers with advanced capabilities to enhance their sales processes and decision-making.

Integrating Relative Efficiency Models with Machine Learning Algorithms for Performance Prediction

Predicting operational performance enables organizations to develop operational effectiveness goals considering different combinations of resources. Measuring performance is consolidated with advances in relative efficiency analysis techniques, including data envelopment analysis (DEA) and stochastic frontier analysis (SFA), albeit these methods lack predictive capability. This paper proposes an approach for performance prediction by integrating relative efficiency measurement models with machine learning algorithms. Data analyses were conducted using data provided by the energy assessment project offered to small and medium-sized manufacturing companies in the United States ( n 7,548) using sales as the output, with the inputs being the number of employees, hours of operation, electricity, natural gas, cost of electricity, and cost of natural gas. Performance was estimated differently, employing parametric (SFA) and non-parametric (DEA) methods. The prediction benchmarking process occurred by adopting machine learning algorithms: regression (LM), support vector machine (SVM), K-nearest neighbor (KNN), linear discriminant analysis (LDA), random forest (RF), and decision tree (DT). The findings showed that it is possible to identify the best prediction algorithm associated with a performance model. However, the performance prediction may differ if different strategies for measuring performance or machine learning model configurations are used. In addition, SFA-LOG and SVM had the best performance for regression, and DEA-VRS/IRS excelled with random forest; the RF algorithm was the best fit across all performance approaches. The error rate depends on the algorithm and the performance model, and the number of classes must be reduced to obtain a higher success rate.

Effect of CSR on Corporate Performance: The Mediating Role of Human Resources Management

The management and marketing literature has increasingly emphasized the significance of corporate social responsibility (CSR) in determining company performance over the past few decades. While there is growing recognition of the potential impact of CSR initiatives on business outcomes, there remains a lack of consensus on the specific mechanisms through which CSR influences performance. This ambiguity underscores the need for further research to elucidate the relationship between CSR and business performance. Our research seeks to address this gap by examining the role of CSR-based human resource management as a potential mediating factor in this relationship. This focus is particularly pertinent given the pivotal role that employees, as key stakeholders, play in shaping organizational outcomes. By analyzing data from a sample of small and medium-sized manufacturing companies using partial least squares structural equation modelling (PLS-SEM), we found evidence supporting the hypothesis that CSR initiatives can positively impact business performance. Importantly, our findings suggest that the effectiveness of a company's CSR strategy in enhancing performance may be contingent upon the extent to which these initiatives are geared towards improving human resource management efficiency. In conclusion, current study contributes to the evolving understanding of the complex interplay between CSR and business performance, highlighting the critical role of human resource management practices in mediating this relationship.

Artificial-intelligence-enabled dynamic demand response system for maximizing the use of renewable electricity in production processes

AbstractThe transition towards renewable electricity provides opportunities for manufacturing companies to save electricity costs through participating in demand response programs. End-to-end implementation of demand response systems focusing on manufacturing power consumers is still challenging due to multiple stakeholders and subsystems that generate a heterogeneous and large amount of data. This work develops an approach utilizing artificial intelligence for a demand response system that optimizes industrial consumers’ and prosumers’ production-related electricity costs according to time-variable electricity tariffs. It also proposes a semantic middleware architecture that utilizes an ontology as the semantic integration model for handling heterogeneous data models between the system’s modules. This paper reports on developing and evaluating multiple machine learning models for power generation forecasting and load prediction, and also mixed-integer linear programming as well as reinforcement learning for production optimization considering dynamic electricity pricing represented as Green Electricity Index (GEI). The experiments show that the hybrid auto-regressive long-short-term-memory model performs best for solar and convolutional neural networks for wind power generation forecasting. Random forest, k-nearest neighbors, ridge, and gradient-boosting regression models perform best in load prediction in the considered use cases. Furthermore, this research found that the reinforcement-learning-based approach can provide generic and scalable solutions for complex and dynamic production environments. Additionally, this paper presents the validation of the developed system in the German industrial environment, involving a utility company and two small to medium-sized manufacturing companies. It shows that the developed system benefits the manufacturing company that implements fine-grained process scheduling most due to its flexible rescheduling capacities.

A multi-skill RCPSP variant for persons with disabilities in sheltered workshops

Sheltered workshops face the challenge of meeting their manufacturing objectives while considering the individual competencies and assistance needs of persons with disabilities. Moreover, work processes in sheltered workshops are weakly structured, allowing for frequent task interruptions and changes based on the preferences of impaired work persons. While the Industry 4.0 literature provides many real-time scheduling algorithms for incorporating multiple objectives and constraints, these algorithms fall short of the characteristics of sheltered workshops. The resource-constrained project scheduling problem (RCPSP) is an optimization problem for computing manufacturing plans considering multiple objectives and resource constraints. Among many different RCPSP variants proposed in the literature, the multi-skill RCPSP (MSRCPSP) variant considers the individual skills of work persons when generating manufacturing plans. With the ongoing digital transformation of enterprises, new assistance systems enter the market, providing individual support to impaired work persons and compensating for lacking skills and abilities.This paper proposes an MSRCPSP variant that incorporates assistance systems and learning tasks compensating for competence gaps in the skill matrix of impaired work persons. Furthermore, it decomposes tasks into individual work objects, which accounts for frequent task interruptions and task preferences of work persons. The algorithm is described and demonstrated using a manufacturing data set from an actual sheltered workshop. In a small evaluation study, the algorithm is tested by scheduling two impaired work persons in the assembly department of a medium-sized manufacturing company in the primary labor market. The evaluation study proves its real-world applicability and the suitability of scheduling algorithms for participation and inclusive work.

“Prepared to Face the Unexpected”: Dynamic Enterprises in Italy as a Model of Resilience

Businesses that demonstrate organizational flexibility, characterized by dynamic problem-solving skills, in-house production processes, and a robust human capital, appear to be successful and resilient in times of crisis. Drawing on my fieldwork in medium-sized manufacturing companies in Emilia, Northern Italy, from June to November 2021, I investigate ideas and characteristics that shed light on good practices, key ingredients of the success of such companies, and possible future models of resilience. I employ participant observation and provide evidence taken from conversations or episodes observed, especially in one of the companies. Although greater structuring is often sought and considered the resolution of many existing problems, non-structuring is, at the same time, convenient in many circumstances. People are essential components in this dynamic organizational model, and their commitment in the organization goes far beyond contractual obligations. Their motivation stems from personal satisfaction as well as from a sense of responsibility and strong personal commitment.

Identifying factors that inhibit or facilitate on-site implementation of chemical risk assessment at small and medium-sized companies.

The introduction and implementation of chemical risk assessment is difficult, especially at small and medium-sized manufacturing and construction companies. This study aimed to identify the factors that inhibit or facilitate such assessment. Twelve individuals in charge of risk assessment at one medium-sized client company and eight small and medium-sized contract companies and responsible for innovation in the manufacturing and construction industries were interviewed. The interview transcripts were analyzed via text mining using KH Corder ver. 3 and a co-occurrence network was used to identify the keywords' connections and each factor in consideration of the interviews. Six factors inhibited or facilitated risk assessment: (1) education on hazardous work in the workplace, (2) improvement suggestions and reduction measures from client and staff, (3) cooperation between employees and contractors in the workplace, (4) thoroughly explanation of SDS content for better understanding, (5) risk awareness based on accident examples, and (6) difficulties imagining the hazards of chemical substances. Factors (1), (2), (3), and (5) were positive, facilitating factors; (4) and (6) were negative, inhibiting factors. This study highlights that it is necessary to educate workers about chemical substance risks using safety data sheets and accident examples in chemical risk assessment.

Mexican MSMEs supplier selection under a commercial and environmental approach: Case Pachuca and suburban areas

The selection of suppliers is a decision that contributes to the competitiveness of companies due to its impact on their costs, efficiency and innovation. The purpose of this research is to distinguish which are the criteria used by a group of Micro, Small and Medium Enterprises (MSMEs) from Hidalgo, Mexico, in order to identify the factors that influence their business and build a supplier evaluation system to guide them to carry out this process with a broader approach than the technical one. The first phase of the investigation includes the search for data from micro, small and medium-sized manufacturing companies, located in four municipalities of the state of Hidalgo, based on information provided by the National Statistical Directory of Economic Units (DENUE). The second stage consists of the application of a questionnaire among the entrepreneurs of the companies. Finally, the third stage included the analysis of the information collected.

Exploring the Relationship Between Circular Economy Practices and Growth in Manufacturing SMEs

The circular economy has been acknowledged as key for manufacturing firms, wishing overcome challenges, particularly relates it to business growth. However, the transition to linear economy at circular economy has been slow in literature, particularly there are relatively few studies that have focused on the relationship of circular economy practices and growth of small and medium-sized manufacturing companies, for this reason this study's main objective is to fill this existing gap in the literature. In addition, a self-administered questionnaire was distributed to a sample of 400 companies in the automotive and auto parts industry in Mexico, analyzing the data set using confirmatory factor analysis and structural equation models. The results obtained follow that the circular economy has a significant positive impact on the growth level of small manufacturing firms in the automotive and autoparts industries.

ANALYSIS OF THE EFFECTIVENESS OF THE INTERNAL CONTROL SYSTEM OVER INVENTORY MANAGEMENT IN MEDIUM-SIZED COMPANIES

This reserach aims to analyze and provide recommendations for improving the effectiveness of the internal control system in inventory management at PT TMT. PT TMT is a medium-sized manufacturing company specializing in elevators and escalators, where inventory serves as the main source of revenue for the company. Having a good internal control is crucial to influence PT TMT's business operations and mitigate existing risks. However, as a medium-sized company, PT TMT faces limitations in resources, infrastructure, and income, which can hinder the implementation of an effective internal control system. This research adopts a qualitative approach that refers to the COSO framework. Data collection techniques include interviews, direct observations, and analysis of PT TMT's Standard Operating Procedures (SOP) documents. Based on the research findings, it was found that PT TMT still has weaknesses in internal control related to the five components of the COSO internal control framework. This study is expected to provide accurate information regarding the internal control condition at PT TMT and offer recommendations to improve the weaknesses in the company's internal control.

Using the Fuzzy Best Worst Method for Evaluating Strategic Planning Models

During the last few decades, various strategic planning models have been suggested in the literature. It is difficult for a company to decide which of these models is most useful to adopt, as each of them shows different strengths and weaknesses. We consider this problem a multicriteria decision problem and investigate the evaluation of six strategic planning models in the context of smaller and medium-sized manufacturing companies in Iran. We consider a methodology that supports the analysis of the input from several decision-makers based on multiple criteria and assume vagueness in the input data elicited from them. For the purpose considered, the fuzzy best worst method (FBWM) appears appropriate. Based on a literature review, six evaluation criteria for strategic management models are considered: formality, clarity, measurability, objectivity, coverage, and consistency. These criteria are evaluated based on the input provided by thirteen managers using linguistic variables. FBWM is used to provide criteria weights that are used to determine fuzzy scores for the six considered strategic planning models. Finally, a defuzzification of the scores indicates the model by Wright is best suited for the application purpose. A consistency analysis included in FBWM shows that the input provided by the managers is sufficiently consistent.

Assessing the New Product Development Process activities in Peruvian medium-sized manufacturing companies

The study focuses on the relationship between the New Product Development Process activities and the success of the new products. Research on this topic is still scarce in emerging countries. From a survey of medium-sized manufacturing companies in Peru, an OLogit regression was used on 140 companies in the Lima and Callao regions. The results indicate that most companies carried out these activities, but only three out of eighteen are decisive for the success of the new product, which minimizes some that are considered key by the theory. This means that this process may not have been well structured or managed. The findings are important not only to improve the efficiency of innovation management, but also to support public policies.

Risk Influence of Employee Productivity on Business Failure: Evidence Found in Serbian SMEs

This research paper analyzes low productivity of company workforce as the key risk factor to business sustainability of a company, with special attention to small and medium-sized companies. The scope of research involves for-profit, and small and medium-sized companies doing business in Serbia. This paper explores whether poor human resource management, and, more particularly, low productivity of employees represent one of the key reasons for poor business performance and eventually failure of the company. The quantitative part of this research was conducted during 2022, by analyzing 468 small and medium-sized companies with less than 250 employees, who ended their business during 2021. Current theory determines human resource management in companies, the influence of different sorts on overall business performance, and employee productivity and its causal effects on business survival. This study attempts to cover identified literature gaps by analyzing the risk influences of low productivity on the failure of small and medium-sized companies, with special diversification between manufacturing and service-oriented companies. Key findings from this research were defined with the help of statistical learning methods, suggesting direct correlation of low productivity in the case of small services-oriented businesses and medium-sized manufacturing companies. Future work on this research includes extension of the analysis to other countries in the West Balkans region and the comparation of all determined causalities.

Critical factors to improve customer satisfaction and reduce operating costs in large and medium-sized manufacturing companies in Nuevo León and the impact caused by the COVID pandemic

<p>The objective of this document is to determine how transportation, trained personnel, customs procedures, preventive maintenance and inventory reliability impact customer satisfaction and operating costs in large and medium-sized companies in the State of Nuevo Leon, Mexico; Likewise, how they were affected by the pandemic caused by COVID. To carry out this research, a measurement instrument was developed, being of a non-experimental, descriptive and longitudinal type, where the results are first evaluated before the pandemic and after the presence of COVID. To analyze the collected information, the structural equation model was used with the method of partial least squares with the SmartPLS3 software. The results are initially presented globally, and later two groups were formed by type of company, those with Mexican and foreign capital; In this way, the approaches of each group and the impact of the factors on the response variables can be evaluated. The results presented in this article are expected to guide companies to improve customer satisfaction and reduce operating costs with and without a pandemic.</p>

Sustainable internal corporate social responsibility and solving the puzzles of performance sustainability among medium size manufacturing companies: An empirical approach

Studies have been conducted within the domain of internal corporate social responsibility, yet less attention has been given to how sustainable internal corporate social responsibility can be employed to accelerate performance sustainability in medium-sized manufacturing companies. Additionally, the culture of internal corporate social responsibility practice in SMEs has been largely ignored by most of the existing studies. This research, therefore, identified the potential influence of work-life balance, wellbeing at workplace, resilience, and job stress on the performance and sustainability of the SME sector. This is achieved through the conceptualization of a research model that empirically tested the influence of four exogenous variables on performance sustainability using data from 270 respondents from Malaysia, having employed Partial Least Square Structural Equation Modeling (PLS-SEM) as a technique of analysis. The results of the study reveal that wellbeing at workplace and job stress as dimensions of sustainable internal corporate social responsibility have a strong influence on performance sustainability. Practitioners can gain valuable insights into how to effectively use workplace wellbeing and job stress to achieve performance sustainability, which is especially important now that SMEs rely heavily on sustainable competitive advantage to stay in business and create value for organizations.

RetrofittAR: Supporting Hardware-Centered Expertise Sharing in Manufacturing Settings through Augmented Reality

Since almost the onset of computer-supported cooperative work (CSCW), the community has been concerned with how expertise sharing can be supported in different settings. Here, the complex handling of machines based on experience and knowledge is increasingly becoming a challenge. In our study, we investigated expertise sharing in a medium-sized manufacturing company in an effort to support the fostering of hardware-based expertise sharing by using augmented reality (AR) to ‘retrofit’ machines. We, therefore, conducted a preliminary empirical study to understand how expertise is shared in practice and what current support is available. Based on the findings, we derived design challenges and implications for the design of AR systems in manufacturing settings. The main challenges, we found, had to do with existing socio-technical infrastructure and the contextual nature of expertise. We implemented a HoloLens application called RetrofittAR that supports learning on the production machine during actual use. We evaluated the system during the company’s actual production process. The results show which data types are necessary to support expertise sharing and how our design supports the retrofitting of old machines. We contribute to the current state of research in two ways. First, we present the knowledge-intensive practice of operating older production machines through novel AR interfaces. Second, we outline how retrofitting measures with new visualisation technologies can support knowledge-intensive production processes.

Impact of cooperation flexibility on innovation flexibility in SMEs

Research background: Flexibility has become a possible means for manufacturing companies to better compete in competitive markets. Furthermore, innovations are perceived as an important factor in company strategy, which can differentiate the company from the competition. Purpose of the article: This present study investigates the problems of cooperation flexibility and innovation flexibility in manufacturing companies among electrical engineering companies in the Czech Republic. The aim of this paper is to identify the impact of cooperation flexibility on innovation flexibility in small and medium-sized manufacturing companies. Methods: A questionnaire addressed to SMEs in the form of the Likert scale was prepared to gather information about cooperation flexibility and innovation flexibility. All parts of the questionnaire were tested using Cronbach Alpha. Spearman correlation and regression analysis were used for analysis. Findings & value added: The results of the research show that external cooperation flexibility and internal cooperation flexibility is related to innovation flexibility in SMEs. Results of the research show that there is a positive relationship 1) between external cooperation flexibility and innovation flexibility and 2) between innovation flexibility and business performance at SMEs. The findings of the research contribute to an understanding of the relationship between cooperation flexibility, innovation flexibility and also innovation performance. The novelty value of this paper lies in its perception of flexibility as having two parts, namely external (with suppliers and customers) and internal cooperation flexibility. In addition, innovation flexibility was investigated in two fields, product, and accompanying services to products. The view mentioned provides a complex view of flexibility.