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The oil and gas industry faces perennial challenges related to cost reduction, product quality enhancement, and operational efficiency. To remain competitive in the market, companies must optimize their production lead times, reduce costs, and ensure high levels of customer service. This study aims to identify and prioritize critical wastes in OCTG production lines to inform operational improvements. This research thoroughly evaluates the existing state of operations and identifies critical areas for improvement by utilizing a combination of Value Stream Mapping (VSM) and Borda Count Methods (BCM). The VSM provides a clear understanding of the complex movement of resources and activities in manufacturing and distributing products, making it easier to identify any inefficiencies. The BCM offers a systematic method to prioritize discovered waste according to its impact and severity. The study's findings expose crucial obstacles and inefficiencies in the production lines of OCTG, with waiting times and defects surfacing as notable areas of concern. By employing BCM, it can prioritize these concerns and derive valuable insights to inform strategic decision-making and operational improvements. The long-term goal of this research is to advance the current efforts of the oil and gas industry in enhancing production processes, reducing costs, and enhancing overall operational efficiency. [ABSTRACT FROM AUTHOR]

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Copyright of Estudios Gerenciales is the property of Universidad ICESI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Brazilian Journal of Production Engineering / Revista Brasileira de Engenharia de Produção is the property of Brazilian Journal of Production Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

SMEs are small to medium-sized businesses with relatively fewer workers and lower revenues than large companies. However, SMEs also contribute to the local economic growth of a region, so the smooth production process needs to be considered to increase productivity. Applying lean manufacturing (LM) and Ergonomics concepts in the production process is critical because it can overcome smooth production and maintain the health and safety of SMEs workers. LM focuses on minimizing waste, while ergonomics focuses on humans as a source of energy in the smooth running of production activities. So, this study aims to measure the level of understanding of Malaysian and Indonesian SMEs workers on applying LM and Ergonomics concepts on the production floor and determine the effect of these two concepts using the SPSS and SmartPLS4 applications. SPSS serves to measure the validity, reliability and mean for the category of workers' understanding of LM and Ergonomics. SmartPLS4 helps us understand the influence of the two concepts. Based on the calculation of the mean for each variable of LM and ergonomics, it is found that Malaysian workers understand enough compared to Indonesian SMEs workers. As for the effect, Ergonomics has a significant influence on LM.

The primary aim of this study is to assess the significance of top management commitment in the context of Lean 4.0 implementation within the pharmaceutical manufacturing industry in Ghana. The study seeks to understand and evaluate the overall effectiveness and achievements associated with adopting Lean 4.0. Employing a positivist mindset, the research utilizes an explanatory quantitative research design and a survey technique. Data collected from 181 employees of pharmaceutical companies in Ghana undergo analysis using SmartPLS (version 4) and IBM SPSS version 26. The study employs a combination of descriptive statistics to summarise data characteristics and inferential statistics to test various hypotheses related to Lean 4.0 adoption. The analysis reveals that the successful integration of lean methods and Industry 4.0 technologies requires meticulous management. Simultaneously, individual implementations of lean principles and Industry 4.0 technologies positively impact business performance. Surprisingly, the study does not observe a substantial positive influence of Lean 4.0 on corporate performance, suggesting that immediate improvements in efficiency or profitability may not result from the adoption of this framework. This research contributes to the field by highlighting the need for careful management in integrating lean methods and Industry 4.0 technologies. It also emphasizes the positive impacts of lean principles and Industry 4.0 technology on business performance. The unexpected finding regarding the lack of immediate improvements in corporate efficiency or profitability with Lean 4.0 adoption prompts considerations of initial implementation challenges or the organization's need for time to adapt to this integrated approach.

Organizing manufacturing work in a way that minimizes delays in individual production operations is a key factor in a highly competitive market. One of the key factors to prevent delays is their correct identification and proper definition of methods to reduce their impact on selected parameters of the production process. The study presents the impact of Lean Manufacturing tools (5S, standardization and Total Productive Maintenance) on delays in the manufacturing process. A statistical analysis of the level of delays was performed, which was aimed at showing the essence of using Lean Manufacturing tools to improve the efficiency of the production process. In the example analyzed, the implementation of selected LM tools allowed for a reduction of delays related to failures by approximately 18 hours.

The global aluminium industry faces a serious challenge in reducing greenhouse gas emissions as the demand for aluminium continues to increase. The aluminium industry has a responsibility to streamline its energy consumption, especially in the production process. There have been many studies discussing energy consumption performance in the industry. However, most of them only discuss energy saving partially, without involving energy consumption with various items produced. This paper proposes an energy savings measurement in the manufacturing industry. An energy baseline consumed per unit volume has been developed using the equivalent volume method with an energy management control system (EMCS). The study takes a case example from the automotiveâaluminium component industry. The steps taken in the study are: examining the production process, converting the production volume to equivalent, calculating the energy consumption ratio, developing an energy baseline, simulating the savings performance, and then proposing an EMCS with key performance indicators (KPI) for sustainability. The results show that the development of a baseline using the ratio of energy and an equivalent volume of production gives a better data correlation with an R2 value close to one. From the baseline, the best­demonstrated performance (BDP) can be used as a reference to set energy goals. Furthermore, the data and the deviant deleted have the same baseline value. They differ in energy reduction goal percentages. The practical application of this study is not only in the manufacturing industry but in other industries as well, such as building management. This study contributes to energy savings achieved with EMCS.

This paper presents a novel lean tool called Project Time Deployment (PTD) whose objectives are to classify, analyse, and eliminate losses in order to reduce production lead time in Engineer-to-Order (ETO) environments. By combining two already known approaches, i.e. the Manufacturing Critical-path Time and the Manufacturing Cost Deployment, PTD identifies the critical losses affecting the project, focusing on the business processes where causal losses occur, and providing opportunities for greater efficiency and effectiveness by reducing or even eliminating them. In ETO projects, the lead time and respecting deadlines are of paramount importance and they are often threatened by several different losses that are difficult to compare. Companies thus need a tool to identify the losses and the tasks where they occur, quantifying them in terms of a single dimension: the time. PTD was designed using a methodology based on four steps: analysis of current solutions, concept design and prototype, proof of concept and validation, and definition of future researches. It was also validated in an industrial implementation concerning an Engineering, Procurement & Construction company operating in the steel industry, and led to an approximate 24% reduction in lead time. [ABSTRACT FROM AUTHOR]

PT XYZ is a leading colored steel company that pioneered the production of colored steel products in Indonesia. To meet consumer demands and improve production lead time, the company faces the challenge of lengthy transition times for roll cleaning and machine setup during product changes. To address this challenge, a research study was conducted to identify lengthy transition processes, wasteful processes during transitions, and necessary improvements to increase production output. Applying a lean manufacturing approach with tools such as the SMED (Single Minutes Exchange of Dies) method, Spaghetti diagram, and swimlane process map, the research began with on-site observations to gather primary data. Subsequently, an analysis was carried out using Process Mapping and waste reduction methods based on the SMED method and the 7 wastes in lean manufacturing. Spaghetti diagrams and swimlane process maps were employed in this analysis. The research has a purpose for deliver action plan for reducing transition processes, including the separation of internal and external activities, automation of roll cleaning, modification of certain isolation items at a specific point, layout changes in the coater room, implementation of multi-skilled operators, and improved job coordination. These activity can reduce 70% of transition time, allowing for an additional production throughput of 4,188.8 tons within one year. This is crucial for maintaining and enhancing the company's production throughput and competitiveness. [ABSTRACT FROM AUTHOR]

Lean manufacturing embraces the principle of doing more with less by removing non-value-added activities from manufacturing processes to preserve effectiveness, flexibility, and profitability. Predictive maintenance in production stages are more critical since it involves machines which are prone to failure and a post failure maintenance stagnates the production which creates bottlenecks due to machine failures. Hence in this work a novel intuitive fuzzy syncretic lean frame work has been implemented to incorporate the need of intelligent systems. The framework is divided into phases which employs Fuzzy logic with embedded smart sensors for effective utilization of man machine and materials in order to improve the effectiveness of a production floor. A novel time based forecasting is done in the design phase which implements the lean tool Takt time. The manufacturing phase uses the sensors to determine the predictive maintenance of the machines thereby implementing continuous flow as the lean tool and the inspection phase uses smart sensor system for real time continuous monitoring of the machining process thereby incorporating Poka-yoke as a lean tool. Thus by implementing the framework the overall equipment effectiveness is achieved which helps in achieving continuous flow of products and defect free products in any production firm. [ABSTRACT FROM AUTHOR]

Continuously adding value to a company's products and services is inevitable in adapting to this evolving and challenging global market. That is why lean philosophy is becoming increasingly important and popular among companies, and they are relying more and more on it. It not only assists in increasing profitability and quality by eliminating all processes that provide no value to the customer but also enables increased flexibility in production and productivity. In this study, the criteria affecting the Lean Maturity Level (LML) were determined, and a lean maturity measurement model, which helps companies define and understand the level of lean maturity and lean effectiveness, was developed. A recently completed case study included data from an online survey with 116 questions, which were conducted on 187 middle to senior-level professionals in Türkiye from different industries. In this model, 9 main and 14 sub-lean criteria were generated to determine LML, and each criterion was weighted based on the assessments of experts. In this paper, the interval-valued spherical fuzzy AHP method is applied for the very first time to the weighting of the criteria of a lean maturity assessment model. After collecting data through an online survey study, Confirmatory Factor Analysis (CFA) in the IBM SPSS AMOS V26 program was applied to test the model fit, validity, and reliability. To determine the LMLs, the leveling scale (understanding, implementation, improvement, and sustainability) was used from the model for LMLs in manufacturing cells. As a result of the analysis of the survey results obtained from the participating companies, the overall LML was calculated as 2.55 out of 4. This result corresponds to the level 3 - improvement range on the leveling scale. The lean maturity success rate of surveyed companies was set at 64%. [ABSTRACT FROM AUTHOR]

Businesses are constantly trying to improve their production by looking for bottlenecks to improve their market position. The introduction and innovation of automated production lines is necessary for both labor shortages and productivity and quality reasons. A combination of precision, fluidity, and speed, that is the basic definition of a production line. With the advent of new technologies, production lines have also begun to continuously speed up and innovate. Innovation is the subject of this paper, where the problem of designing a completely new layout for a new production line in the food industry has been addressed. The aim of this paper was to create a design for the optimal layout of the production line in preselected production areas. Optimal use of the space allocated for production is very important for every company today. [ABSTRACT FROM AUTHOR]

This study aims to investigate the relationship between sustaining factors and lean manufacturing implementation. This survey-based study was a cross-sectional study and the samples were drawn by using cluster sampling procedure from medium and large manufacturing companies based on the Federation of Manufacturers Malaysia (FMM) with the final number of 151 respondents. In total, four hypotheses were developed and tested statically using PLS-SEM through SmartPLS software. The result provided evidence that lean culture, lean leadership, and lean knowledge management have a positive relationship on lean manufacturing implementation. However, lean supplier management does not have a positive relationship on lean manufacturing implementation. The survey was responded by middle and top-level management from the discrete manufacturing industries. Although there is growing interest in empirical shreds of evidence in favor of sustaining lean, this study provides a comprehensive view of sustaining factors for lean manufacturing implementation. Hence, this study contributes to expanding the boundary of the existing literature and contributes to the body of knowledge while providing insights to practitioners in tailoring strategies to sustain lean manufacturing implementation and leverage their performance. [ABSTRACT FROM AUTHOR]

Currently, the concept of lean manufacturing has covered almost the entire global industry and all its sectors. This is due to the effectiveness of this concept, since with its application, along with increased productivity and quality, more products are produced with the same amount of resources and at lower costs. Today, lean manufacturing in the context of Industry 4.0 is relevant for achieving the principles of sustainable development. The purpose of the study is to analyze the features of lean manufacturing in the context of Industry 4.0 to achieve the principles of sustainable development. The paper considers the main theoretical aspects of the introduction of lean manufacturing in industrial enterprises and examines the essence and characteristics of Industry 4.0. Based on an expert survey, Industry 4.0 technologies have been identified for the implementation and support of lean manufacturing. The study concludes that the introduction of Industry 4.0 technologies, such as enterprise resource planning systems, industrial Internet of Things, automation and robotics, augmented and virtual reality, and radio frequency identification in industrial enterprises, into lean manufacturing not only lead to a reduction in losses but also serves as the best way to eliminate them. Flexible forecasting of changes in the supply and demand of a product helps to plan production volumes more accurately, which allows manufacturers to avoid further surpluses and losses. [ABSTRACT FROM AUTHOR]

Automotive companies are facing major challenges, namely competitiveness and the evolution that characterizes the sector. To ensure their sustainability, companies operating in the automotive industry are concentrating their efforts on reducing waste sources throughout the supply chain by implementing a variety of Lean Management tools. The compliance of the quality management system with the requirements of the international automotive standard IATF 16949:2016 is also a top priority for automotive suppliers. IATF certification is required to operate in the automotive market and enables organizations to meet customer requirements and demonstrate the quality assurance of their systems. This paper analyzes the principles of the Lean Management organizational tools in correlation with the requirements of the IATF automotive standard and determines their synergistic impact on operational excellence. Based on the correlation analysis performed, an original roadmap that will serve as a guide for automotive companies has been developed. The findings show that in order to achieve operational excellence, it is necessary to implement the five Lean Management organizational tools in correlation with the operational requirements dictated in chapter 8 as well as the leadership requirements outlined in chapter 5 of the international automotive standard. [ABSTRACT FROM AUTHOR]

In the current era is increasing intention for identifying and mitigating production bottlenecks, particularly in industrial enterprises, by optimizing material and information within the broader context of enterprise logistics. In industrial practice, when applying lean management or any innovation i.e. change in the production process, a common problem is the lack of knowledge of the value stream as a complete system. The efforts of industrial engineers to streamline material flow and warehouse management are closely linked to the reduction of financial resources associated with operations. The paper is focused on improving performance of production process though material flow and storage efficiency increase. The aim of this paper is to describe the implemented analysis of the material and information flow of a selected product and explain the proposed solution to streamline the warehousing system in an industrial enterprise. Desired result was to adjust the size of warehouse at the line, to save production space and to optimize production process in order to maximize the proportion of time in which value is added to the product in the total continuous production time. Different methods (mathematical-statistical calculations, MIFA analysis, MIFD method, guided interview method, observation, GEMBA walk) have been used in the analysis of the current situation. In current turbulent times, when industrial enterprises are pushed to continuously innovate in order to reduce warehousing capacities, it is necessary to continuously improve performance in the context of sustainable business. [ABSTRACT FROM AUTHOR]

Lean Manufacturing has become, in recent years, one of the most important philosophies for improving production and organizational systems. The literature shows that Hesitant Fuzzy Linguistic Terms Sets (HFLTSs) are highly capable of manipulating the uncertainty that the judgments made by evaluators carry and that they are subject to their perception, especially when used in combination with multicriteria decision making (MCDM) for the measurement of indicators in this type of system, as well as their general performance. However, it is still of interest to researchers to develop techniques and instruments that facilitate the measurement of the results obtained after applying this philosophy in organizations. This article proposes a model for the evaluation of the Lean Manufacturing performance through the Analytic Hierarchy Process (AHP) and Dimensional Analysis (DA) using HFLTSs. The results obtained show that the proposed model is a solid tool for the evaluation of Lean Manufacturing systems from a different perspective and that it can be integrated into the issuance of evaluations in a better way by considering human subjectivity. At the same time, it offers a strategy to create priorities in the action plans that Lean system managers propose after evaluating. However, it is important to apply the proposed model to multiple organizations and analyze the results obtained to maximize its benefits. [ABSTRACT FROM AUTHOR]

Furniture production is a specific industrial sector with a high human labor demand, a wide range of materials processed, and short production runs caused by high customization of end products. The difficulty of measuring the aesthetic requirements of customers is also specific to furniture. This review of academic papers identifies and explains effective quality management strategies in furniture production. The reviewed literature highlights a range of quality management methodologies, including concurrent engineering (CE), total quality management (TQM), lean manufacturing, lean six sigma, and kaizen. These strategies encompass a variety of pro-quality tools, such as 5S, statistical process control (SPC), quality function deployment (QFD), and failure mode and effects analysis (FMEA). The strengths of these quality management strategies lie in their ability to enhance efficiency, reduce waste, increase product diversity, and improve product quality. However, the weaknesses concern implementation challenges and the need for culture change within organizations. Successful quality management in furniture production requires tailoring strategies to the specific context of the furniture production industry. Additionally, the importance of sustainability in the furniture industry is emphasized, which entails incorporating circular economy principles and resource-efficient practices. The most important finding from the literature analysis is that early detection and correction of poor quality yields the most beneficial outcomes for the manufacturer. Therefore, it is essential to strengthen the rigor of quality testing and analysis during the early stages of product development. Consequently, a deep understanding of consumer perspectives on required furniture quality is crucial. The review identified two research gaps: (1) the impact of unnecessary product over-quality on the efficiency of furniture production and (2) the influence of replacing CAD drawings with a model-based definition (MBD) format on quality management in furniture production. [ABSTRACT FROM AUTHOR]

Small and medium enterprise (SME) manufacturers are impeded from participating in sustainability initiatives using new technologies due to the high cost and the lack of clarity on where to start. The integration of low-cost digital solutions has enabled SME manufacturers to adopt Industry 4.0 technologies to support operations. However, using low-cost technologies to address sustainability challenges is underexplored. This article addresses three key research questions: What digital solutions do SMEs need to address industrial sustainability challenges? To what extent can existing low-cost digital solutions be used to address industrial sustainability challenges? How should new digital solutions for developing greater sustainability be prioritised? Three main tasks were conducted. Initially, a new sustainability-focused sub-catalogue was created using an existing catalogue of low-cost solution areas for manufacturing. Secondly, a workshop with 17 participants was used to identify the top ten priority solution areas, with process monitoring, energy monitoring, and quality inspection at the top. Lastly, existing low-cost digital solutions within the top ten priority areas were evaluated to identify how they could contribute to lean manufacturing. Predominantly existing solutions could contribute to waste or use reduction in lean manufacturing. This study provides a foundation for the future development of low-cost solutions for sustainability by indicating manufacturers' key priority areas and outlining how existing solutions could be adapted to support waste reduction. [ABSTRACT FROM AUTHOR]

This study develops an integrated classic-interval-valued fuzzy TOPSIS approach to assess performance of different departments of a hospital. Although the concept of performance measurement has been discussed in previous studies, its concurrent integration with lean, agile, and green strategies is less investigated. Therefore, this research has been completed in three linked phases as follows. Firstly, the critical metrics of lean, agile, and green strategies are extracted from previous literature. Secondly, a fuzzy TOPSIS approach is developed to compare three departments of a hospital using the investigated metrics of previous phase. According to the obtained results of this phase, the eye, and emergency departments are the best and worst departments, respectively. Next, the obtained results are checked by an interval-valued fuzzy TOPSIS approach for further investigation in the third phase. Similarly, approving the previous results, eye department provides the best performance according to the second approach. As a contribution, this research showed that different MCDM techniques might provide a same result. Furthermore, the developed methodology can be applied to assess and compare the performance of different departments. [ABSTRACT FROM AUTHOR]

This paper presents an integrated framework that combines the strengths of three relevant business excellence philosophies: Theory of Constraints, Lean, and Six Sigma (TLS). The integrated framework increases the TLS Orientation of a firm when management employs a unique growth-oriented mindset, adopts global measurements, and implements an integrated continuous improvement methodology. We discuss how a small-to-medium enterprise (a real but disguised manufacturing firm in India) implemented the proposed framework by employing the cognate key concepts and tools in an integrated manner, and improved its business excellence in terms of improved flow, reduced waste, and increased process capability, which, in turn, strengthened its financial performance. We conclude the paper by discussing the limitations of the study (e.g. an application in a small business) and providing future research directions to further develop its underlying theory and validate the proposed TLS orientation construct by means of case studies and questionnaires. Some initial results are reported. [ABSTRACT FROM AUTHOR]

In response to the global surge in industrial competition, organizations have increasingly embraced lean green practices as an approach to identify and eliminate non-value-added waste in manufacturing processes, while ensuring sustainable practices. This research extends current literature on lean green practices in manufacturing by a) exploring current implementation of lean green practices in the automotive components manufacturing industry and b) examining the challenges encountered within its supply chain processes when implementing the practices. The evaluation utilizes the SCOR model, and a focus group of automotive components manufacturing professionals in the UK. The findings reveal that an average level of implementation of lean green practices, offering benefits such as enhanced productivity, cost reduction, and improved competitive advantage. Implementation challenges were found to be particularly faced in the sourcing and manufacturing (MAKE) processes of the supply chain, due largely to component outsourcing issues, and inefficiencies in the conversion of raw materials into finished products to meet supply chain demands. [ABSTRACT FROM AUTHOR]

he literature on Lean Manufacturing has predominantly emphasized mass production and batch systems, leaving a considerable knowledge gap regarding the challenges and considerations specific to implementing Lean principles in Engineer-to-Order (ETO) manufacturing contexts. This paper addresses this gap by exploring the interaction between Project Cost Deployment (PCD), a tailored method for ETO environments, and the digital technologies of Industry 4.0. The research aims to identify the synergies between Lean Manufacturing and Industry 4.0, investigating how their integration can enhance productivity, quality, and competitiveness in the manufacturing industry. While Lean Manufacturing is adept at addressing loss reduction and elimination across various industrial contexts, Industry 4.0 leverages digital technologies to revolutionize manufacturing operations and enable more efficient and intelligent production systems. The paper demonstrates the effectiveness of the PCD method through an industrial application involving an international company specializing in customized paper converting machinery and lines. By utilizing PCD in conjunction with Industry 4.0 technologies, analysts were able to uncover hidden losses and quantify them from an economic perspective, while also evaluating the potential impacts of improvement activities. The results highlight the significance of synergizing Lean Manufacturing and Industry 4.0 for ETO environments, offering valuable insights into how digital technologies can be effectively integrated into Lean principles. [ABSTRACT FROM AUTHOR]

In the production planning and control field, assessing the performance of a manufacturing system is a multi-dimensional problem in which neglected dimensions may lead to hidden inefficiencies and missed opportunities for gaining a competitive advantage. In this paper, a new data formalization method is proposed to model a manufacturing system by simultaneously considering value creation and technical, economic, and environmental performance. The proposed method combines the principles of Material Flow Analysis and a new data structure that exploits some characteristics of the Multi-layer Stream Mapping and the Enterprise Input-Output methods to obtain a data-driven approach, typical of Industry 4.0. The proposed method can deal with complex systems and allows to consider also non-value-added activities such as transport and inventories. The implementation of the method and its advantages are shown through a numerical example based on a recycled plastic pipeline manufacturing system. The method shows positive synergies and mutual benefits between sustainable production, lean principles, and data-driven approaches and technologies of Industry 4.0. The method improves the alignment of environmental, technical, economic, and value creation information between operational and strategical levels, removing redundancies in data collection, conditioning, and processing activities, thus reducing partial information, hidden risks and opportunities, and inconsistencies. [ABSTRACT FROM AUTHOR]