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With the rapid development of the sharing economy in manufacturing industries, manufacturers and the equipment suppliers frequently share capacity through the third-party platform. This paper aims to study influences of manufacturers sharing capacity on the supplier and to analyze whether the supplier shares capacity as well as its influences.

This paper deals with conditions that the supplier and manufacturers share capacity through the third-party platform, and the third-party platform competes with the supplier in equipment sales. Considering the heterogeneity of the manufacturer's earning of unit capacity usage and the production efficiency of manufacturer's usage strategies, this paper constructs capacity sharing game models. Then, model equilibrium results under different sharing scenarios are compared.

The results show that when the production or maintenance cost is high, manufacturers sharing capacity simultaneously benefits the supplier, the third-party platform and manufacturers with high earnings of unit capacity usage. When both the rental efficiency and the production cost are low, or both the rental efficiency and the production cost are high, the supplier simultaneously sells equipment and shares capacity. The supplier only sells equipment in other cases. When both the rental efficiency and the production cost are low, the supplier’s sharing capacity realizes the win-win-win situation for the supplier, the third-party platform and manufacturers with moderate earnings of unit capacity usage.

This paper innovatively examines supplier's selling and sharing decisions considering manufacturers sharing capacity. It extends the research on capacity sharing and is important to supplier's operational decisions.

Equipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.

The research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.

The findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.

Manufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.

The study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.

This paper establishes a quality model for automation assembly of range hood impeller based on generalized grey relational degree, it improves the debugging efficiency of the newly developed assembly workstation.

First, spot check the trial production impellers and obtain three indexes that reflect the assembly quality of the impellers. Then, analyze the parameters that affect the assembly quality of the impeller using grey relational analysis (GRA), establish a model for the assembly quality of the range hood impeller based on the generalized grey relational degree and identify the main parameters. After that, analyze the transmission structure of automation assembly workstation, identify the reasons that affect parameters and propose improvement plans. Finally, a trial production is conducted on the automation assembly workstation after adopting the improved plan to verify the quality model of impeller automation assembly.

The research shows that compared to manual assembly, the automation assembly quality of the impeller using GRA model has been improved, shortening the debugging cycle of the newly developed assembly workstation.

The newly developed automation equipment will have some problems in the trial production stage, which often rely on the experience of engineers for debugging. In this paper, the automation assembly quality model of range hood impeller based on GRA is established, which can not only ensure the quality of finished impeller but also shorten the debugging cycle of the equipment. In addition, GRA can be widely used in the commissioning of other automation equipment.

This study has developed a set of impeller automation assembly workstation. The debugging method in the trial production stage is beneficial to shorten the trial production time and improve the economic benefits.

The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.

This study aims to identify the relationship between different maintenance practices and productive efficiency in continuous process productive plants as well as the moderating effect of good training practices.

The empirical data were drawn from a database containing 609 observations of 29 productive units. Scales were validated using the Q-sort method. The panel data technique was used as the analysis methodology, with the inclusion of fixed effects for each productive plant.

Maintenance practices can effectively contribute to increasing the overall equipment effectiveness (OEE) of firms. Application of predictive maintenance practices should be considered as the primary training tool.

This study used a secondary database, limiting the research design and data manipulation.

The article provides practitioners with an analysis of maintenance practices by category (predictive, preventive and corrective), and the impact of each practice on the OEE of continuous process productive plants. Moreover, it explores the importance of training for extracting more results from maintenance practices.

Companies are investing in new technologies, but it is also essential to invest in training people. There is a demand for Industry 4.0 through the introduction of upskilling and reskilling programs.

This study used practice-based view (PBV) theory to explain how maintenance practices help firms achieve greater OEE. Furthermore, it introduced training practice as a moderating variable in the relationship between maintenance practices and OEE.

Lean manufacturing, a philosophy that revolutionized the manufacturing industry, is often linked to the Toyota Production System (TPS). At the core of a lean company, one can observe proper implementation of lean manufacturing tools and practices such as just-in-time, work teams, cellular manufacturing, lean layout, etc. The goal of lean production is to minimize the waste producing activities while offering the same or enhanced quality to customers.

The aim of this research is to investigate the implementation degree of lean manufacturing and its tools and practices focusing on the case of an SME in Albania as a concrete example. Higher attention is given to some of the pillars of lean manufacturing such as just-in-time and cellular manufacturing.

In this case study, researchers observed a variety of features of lean production. Just-in-time was implemented to a certain extent and cellular manufacturing at a more surprising level, which was facilitated especially by the U-shaped facility layout designs observed during the site visits. The value stream mapping showed a proper group technology in place and the management displayed signs of engagement and future advancement desire regarding this philosophy.

Refractory materials are now used in all major industries that demand high-temperature resistance, including petrochemicals, steel, cement and aviation. Businesses must decrease operating costs, enhance product technology, sell well and manage corporate risks in decision-making, notably supplier selection, to be more competitive. The study aims to determine the key criteria and factors of supplier selection and to evaluate the importance of the key factor of the supplier selection criteria for the refractory materials manufacturers in Taiwan.

Analytical hierarchy process (AHP) is used to rank these factors for the decision maker. The AHP method is suitable for verifying refractory supplier selection criteria and providing references. The weighted loss scores for each supplier are then determined using the relative importance as the weights. Supplier selection criteria are ranked using their aggregate weighted loss scores. The provider with the lowest loss score should be chosen.

Product quality is the most significant of the five criteria: product quality, production technology, logistics capacity, service capability and supplier background. Professionalism is the most significant aspect of product quality, whereas equipment and capacity are vital in manufacturing techniques. The studies also show that the delivery rate is essential for logistics and service capabilities.

This research has important implications for refractory suppliers in promptly fine-tuning the production and service to enhance customer satisfaction, which is key to business sustainability.

The application of an AHP technique to a real-world industrial issue is what makes this research unique. This research addressed one of the most critical topics in supply chain operations by offering better judgement for supplier selection via the use of suitable quantitative methodologies.

This study aims to investigate routines as a conceptual tool to analyze resources management in small and medium-sized enterprises’ (SMEs) productive processes.

The authors developed a qualitative multiple case study with Brazilian companies in the bakery industry. Data were collected through interviews, on-site observation and documentary analysis. Plus, the authors used business process modeling (BPM) techniques to map the observed routines.

The restrictions of SMEs accentuate the improvisation of routines. However, contrary to expected, many of these deviations expand the possibilities of organizational action as they become successful in terms of operational efficiency, which allows these companies to extract performance from ordinary resources and imitable management practices.

The BPM shows its value to track the allocation of resources in SMEs by recording the evolution of its routines and helping to preserve an operational memory. This finding could be useful to help public agencies to develop accessible management tools to assist small business owners.

Most of the conceptual tools developed to analyze the resources management are based on the study of large organizations, which may limit the analysis and lead to restricted or mistaken results if used in another context without proper adaptation. The authors apply an objective and representational epistemological lens to organizational routines to adapt it to the pragmatic context of operations management. Also, the authors suggest that better than a resource-based view, the practice-based view is a theoretical approach more compatible with the resource constraints context of SMEs.

In order to analyze the level of independent controllability and its evolution of high-end equipment manufacturing industry from Jiangsu Province, this article introduces the dual-excitation control line method to construct a comprehensive evaluation model for independent controllability.

Through the collection of information of high-end equipment manufacturing industry's independent and controllable capabilities on different indicators, the three aspects of advancement, autonomy and controllability, an empirical evaluation of 10 enterprises in the high-end equipment cluster in Jiangsu Province was conducted in terms of advancement, autonomy and controllability.

It effectively reveals the area and evolution characteristics of the “reward” and “punishment” of different indicators of each representative enterprise and reflects the development status and different characteristics of each representative enterprise on the three indicators. The research results provide decision-making guidance for enterprises in the management and control of advanced manufacturing systems with independent and controllable capabilities.

Existing research focuses on the evaluation of enterprises' independent controllability only on a single angle or index. This paper maps the dynamic evaluation problem of multiple time-point data to the evaluation problem of single time-point multi-index data and investigates the fluctuation of the performance of the same enterprise under different indexes, so as to comprehensively evaluate the independent controllable level of high-end equipment manufacturing industry and analyze the reasons. Further, this paper first establishes an evaluation index system of independent controllable level of high-end equipment manufacturing industry and quantitatively measures the advanced, independent, controllable and other aspects of typical enterprises in this industry by constructing a double incentive control line evaluation model.

This study investigates the integration of Industry 4.0 (I4.0) technologies with condition-based maintenance (CBM) in upstream oil and gas (O&G) operations, focussing on developing countries like Nigeria. The research identifies barriers to this integration and suggests solutions, intending to provide practical insights for improving operational efficiency in the O&G sector.

The study commenced with an exhaustive review of extant literature to identify existing barriers to I4.0 implementation and contextualise the study. Subsequent to this foundational step, primary data are gathered through the administration of carefully constructed questionnaires targeted at professionals specialised in maintenance within the upstream O&G sector. A semi-structured interview was also conducted to elicit more nuanced, contextual insights from these professionals. Analytically, the collected data were subjected to descriptive statistical methods for summarisation and interpretation with a measurement model to define the relationships between observed variables and latent construct. Moreover, the Relative Importance Index was utilised to systematically prioritise and rank the key barriers to I4.0 integration to CBM within the upstream O&G upstream sector.

The most ranked obstacles in integrating I4.0 technologies to the CBM strategy in the O&G industry are lack of budget and finance, limited engineering and technological resources, lack of support from executives and leaders of the organisations and lack of competence. Even though the journey of digitalisation has commenced in the O&G industry, there are limited studies in this area.

The study serves as both an academic cornerstone and a practical guide for the operational integration of I4.0 technologies within Nigeria's O&G upstream sector. Specifically, it provides an exhaustive analysis of the obstacles impeding effective incorporation into CBM practices. Additionally, the study contributes actionable insights for industry stakeholders to enhance overall performance and achieve key performance indices (KPIs).