Improving Manufacturing Performance Research Articles

Green manufacturing performance improvement under uncertainties: An interrelationship hierarchical model

Green manufacturing is a developing industrial trend that addresses environmental issues and has a long-term, realistic, and sustainable future. However, previous studies involving the attributes that are essential for green manufacturing performance improvement, particularly, in the textile industry, are lacking. Identifying a set of green manufacturing attributes and hierarchical causal interrelationships that deliver insights into performance improvement under uncertainties is necessary. Hence, this study aims to create a reliable hierarchical model and to identify the causal interrelationships between green manufacturing attributes using a hybrid approach consisting of the fuzzy Delphi method (FDM), fuzzy decision-making trial and evaluation laboratory (FDEMATEL), and analytic network process (ANP). The green manufacturing model, which includes five aspects and 23 criteria, is verified. Green operational practices, government policy and environmental management constitute the group that strongly affects manufacturing performance. In terms of practices, manufacturers should focus on clean technology, green processes, lifecycle management, waste recycling, and textile waste generation and management. These criteria will help the textile industry in Vietnam to become more sustainable and environmentally friendly since the most important criteria involve realizing green manufacturing.

Implementation of Total Productive Maintenance in a Jute Bag Industry:a Case Study

In this competitive world, manufacturing industries are suffering from several problems such as breakdown of machine, production adjustments, poor working of defective equipment, poor maintenance and management, unhealthy working area and this lead to low productivity, increasing wastage, fire damage and major losses in the company’s growth. Total Productive Maintenance (TPM) approaches can be promising solution to overcome these problems. Therefore, this study attempts to evaluate the contributions TPM initiatives towards improving manufacturing performance in a Jute bag manufacturing industry in Bangladesh. Specific objectives of this study are identification and reduction of major losses by using TPM tools and evaluation of the effectiveness by analyzing Overall Equipment Efficiency (OEE). The correlations between various TPM implementation dimensions and manufacturing performance improvements have been evaluated and validated by employing overall equipment effectiveness (OEE) in the jute bag plant. In this study TPM tools such as 5S, Autonomous Maintenance, Kobetsu Kaizen, Planned Maintenance and Education and Training have been implemented in the selected company. The equipment failure losses are reduced 3.85% through continuous improvement concept. The defect rate is reduced by 1.84% by taking preventive action. Most importantly it is observed that the OEE is improved from 7.42% i.e improved the productivity as well as improved the quality of product. Journal of Engineering Science 14(1), 2023, 137-149

Industry 4.0 and Smart Manufacturing: Exploring the integration of advanced technologies in manufacturing

Industry 4.0 and Smart Manufacturing represent a paradigm shift in the manufacturing landscape, driven by the integration of cutting-edge technologies. This study explores the seamless integration of advanced technologies, including the Internet of Things (IoT), artificial intelligence (AI), and data analytics, in manufacturing processes to enhance efficiency, productivity, and decision-making. By connecting physical and digital systems, Industry 4.0 enables real-time data exchange and intelligent decision-making, leading to optimized production processes and resource utilization. The implementation of IoT devices and sensors empowers predictive maintenance, quality control, and enhanced visibility across the supply chain. Additionally, AI-driven predictive modeling and data analytics enable data-driven insights, facilitating agile decision-making and improved manufacturing performance. This investigation delves into the transformative potential of Industry 4.0 and Smart Manufacturing, offering valuable insights into the future of manufacturing industries.

Efficiency measurement based on novel performance measures in total productive maintenance (TPM) using a fuzzy integrated COPRAS and DEA method

Total Productive Maintenance (TPM) has been widely recognized as a strategic tool and lean manufacturing practice for improving manufacturing performance and sustainability, and therefore it has been successfully implemented in many organizations. The evaluation of TPM efficiency can assist companies in improving their operations across a variety of dimensions. This paper aims to propose a comprehensive and systematic framework for the evaluation of TPM performance. The proposed total productive maintenance performance measurement system (TPM PMS) is divided into four phases (e.g., design, evaluate, implement, and review): i) the design of new performance measures, ii) the evaluation of the new performance measures, iii) the implementation of the new performance measures to evaluate TPM performance, and iv) the reviewing of the TPM PMS. In the design phase, different types of performance measures impacting TPM are defined and analyzed by decision-makers. In the evaluation phase, novel performance measures are evaluated using the Fuzzy COmplex Proportional Assessment (FCOPRAS) method. In the implementation phase, a modified fuzzy data envelopment analysis (FDEA) is used to determine efficient and inefficient TPM performance with novel performance measures. In the review phase, TPM performance is periodically monitored, and the proposed TPM PMS is reviewed for successful implementation of TPM. A real-world case study from an international manufacturing company operating in the automotive industry is presented to demonstrate the applicability of the proposed TPM PMS. The main findings from the real-world case study showed that the proposed TPM PMS allows measuring TPM performance with different indicators especially soft ones, e.g., human-related, and supports decision makers by comparing the TPM performances of production lines and so prioritizing the most important preventive/predictive decisions and actions according to production lines, especially the ineffective ones in TPM program implementation. Therefore, this system can be considered a powerful monitoring tool and reliable evidence to make the implementation process of TPM more efficient in the real-world production environment.

A study of challenges in successfully implementing maintenance practices in northern Indian small and medium manufacturing companies

PurposeThis study aims to prioritize barriers responsible for impeding the successful implementation of maintenance practices in Northern Indian small and medium enterprises (SMEs). Maintenance practices play a crucial role in a company's long-term competitiveness in the manufacturing sector, significantly affecting production, quality and cost. Maintenance practices are equally vital in SMEs, because SMEs are the heart of the large industries, as these units are dependent on SMEs for their parts and sub-assemblies. However, due to many obstacles, SMEs have been confronted with various challenges in implementing maintenance practices.Design/methodology/approachFirst, a review of the published articles and survey of 216 Indian organizations has been conducted to identify the maintenance implementation barriers in SMEs. The Pareto analysis and the VlseKriterijumska Optimizcija Kompromisno Resenje in Serbian (VIKOR) approach have been deployed to rank the significant challenges in implementing maintenance practices in Northern Indian SMEs.FindingsThe present study aims to recognize and rank the barriers to effective maintenance implementation practices in SMEs, in order to initiate appropriate corrective actions to improve maintenance function performance.Originality/valueThe study will help maintenance managers in preparing an action plan to overcome the obstacles to maintenance practice's performance for realizing significant manufacturing performance improvements.

A digital twin based framework for detection, diagnosis, and improvement of throughput bottlenecks

Digitalization through Industry 4.0 technologies is one of the essential steps for the complete collaboration, communication, and integration of heterogeneous resources in a manufacturing organization towards improving manufacturing performance. One of the ways is to measure the effective utilization of critical resources, also known as bottlenecks. Finding such critical resources in a manufacturing system has been a significant focus of manufacturing research for several decades. However, finding a bottleneck in a complex manufacturing system is difficult due to the interdependencies and interactions of many resources. In this work, a digital twin framework is developed to detect, diagnose, and improve bottleneck resources using utilization-based bottleneck analysis, process mining, and diagnostic analytics. Unlike existing bottleneck detection methods, this novel approach is capable of directly utilizing enterprise data from multiple levels, namely production planning, process execution, and asset monitoring, to generate event-log which can be fed into a digital twin. This enables not only the detection and diagnosis of bottleneck resources, but also validation of various what-if improvement scenarios. The digital twin itself is generated through process mining techniques, which can extract the main process map from a complex system. The results show that the utilization can detect both sole and shifting bottlenecks in a complex manufacturing system. Diagnosing and managing bottleneck resources through the proposed approach yielded a minimum throughput improvement of 10% in a real factory setting. The concept of a custom digital twin for a specific context and goal opens many new possibilities for studying the strong interaction of multi-source data and decision-making in a manufacturing system. This methodology also has the potential to be exploited for multi-objective optimization of bottleneck resources.

Waste Analysis in the Speaker Box Assy Process to Reduce Lead Time in the Electronic Musical Instrument Industry

Purpose: This study aims to analyse the waste in the production line to get an efficient production lead time. Methodology/Approach: This research uses the integration method of value stream mapping and kaizen. Based on the analysis with expert judgment, it is known that the waste comes from an inefficient factory layout. Improvements by making changes to factory layouts and merging workstations. Findings: This research has found waste caused by ineffective factory layouts based on Focus Group Discussions (FGD). Improvements by incorporating workstations and changes to the factory layout can reduce production lead time. The results showed that the production lead time decreased from 3.21 days to 2.31 days or a decrease in the ratio of 31.15%. Research Limitation/Implication: This research can also improve manufacturing performance such as cost efficiency, efficient layout, and labour reduction. So for similar companies, this research can be a reference for making improvements in reducing waste that can improve manufacturing performance so that they can compete in national and international markets. Originality/Value of paper: This paper provides benefits for the musical instrument industry regarding waste reduction. According to this research, lean production can increase the productivity and quality of the production system, because it can eliminate the waste of time or the production process. The new approach of this research is used the integration methods by involving experts through FGDs to make improvements and reduce waste in the production line.

A Decision-Making Model for Predicting Technology Adoption Success

Advanced manufacturing technology (AMT) has the potential to significantly improve manufacturing performance and boost competitiveness in the global market. Investment in AMT remains a promising but potentially risky venture due to the numerous factors that must be considered before the full benefits of implementing a new technology can be realized. To respond to the reported risks and uncertainties, such as those revealed in the recent industrial revolution, it is very important to identify and classify the critical factors that can influence the success of AMT adoption early in the planning stage. Based on an extensive review of relevant literature, 32 critical factors are identified and classified into ten categories in this paper. A new multiple-input single-output (MISO) model is developed by combining the fuzzy Delphi method (FDM) and the fuzzy inference system (FIS) based on the objectives defined. The FDM is used to determine the critical factors, and the FIS addresses the general fuzzy multi-attribute decision-making (MADM) problem in order to evaluate and predict the percentage of AMT adoption success with an existing system. The model is validated using a numerical test bed, and the results show that the model is a proper tool for risk management in AMT implementation.

ORGANIZATIONAL CULTURE TRANSFORMATION MODEL IN A MANUFACTURING PLANT: IMPACT ANALYSIS OF A FOUR YEAR JOURNEY TOWARDS HIGH PERFORMING ORGANIZATION

The current market environment, characterized by its volatility, uncertainty, complexity and ambiguity (VUCA), means a paradigm shift for any organization. Consequently being innovative via new perspectives such as the management of the Organizational Culture becomes a key factor as a potentially strong competitive advantage. In this framework, the main objective of this research is to analyse the impact of an Organizational Culture Transformation Model for an automotive sector’s manufacturing plant, with over 750 employees and 105,000 m2 in size, to facilitate its journey towards a High Performing Organization as way of survival. After four years of rigorous and systematic implementation of the model, the impact has been measured through the improvement obtained in the main business Key Performance Indicators and the Organizational Culture survey. In all of them, improvement exceeds expectations. Thus, Net Structural Cost Savings have been 1.4% versus 1% expected, Plant Overall Equipment Efficiency 69.8% vs 68%, for the Safety and Quality Index, Line Driven Management has been implemented as expected, and finally the Organizational Culture Survey (% of questions answered 4 or 5) has reached 58.1% vs 55%, demonstrating that the model positively impacts the organizational culture, enabling the viability of the plant. Keywords: Organizational Culture, High Performance Organization, Manufacturing Performance Improvement, Key Performance Indicators

Improving manufacturing performance through green SCM in Indian manufacturing industries

Improving manufacturing performance through green SCM in Indian manufacturing industries

Integration of Waste Assessment Model and Lean Automation to Improve Process Cycle Efficiency in the Automotive Industry

Purpose: This study aims to improve Process Cycle Efficiency (PCE) by reducing waste in the assembly production line. This research is a case study conducted in a four-wheel vehicle manufacturing company to create a Lean production system. Methodology/Approach: This study uses the Waste Assessment Model (WAM) and Lean Automation integration methods carried out by 5 expert judgements in the selected four-wheeled vehicle industry. Findings: Based on the WAM method, this study found the biggest waste on the assembly line, namely transportation with a percentage of 20.44%. Improvements made with Lean Automation can increase the value of PCE from 56.76% to 63.62%. Research Limitation/Implication: This research is limited to one model, namely Multi Purpose Vehicle (MPV). This research provides benefits for companies related to waste reduction. For similar companies, this research can be input for manufacturing practitioners in improving manufacturing performance to compete in the global market. This Lean production can reduce manpower which has an impact on saving production costs. Originality/Value of paper: This paper provides added value related to the application of Lean terminology which aims to improve industrial automation-based manufacturing companies.

Prospects of Wireless Energy-Aware Sensors for Smart Factories in the Industry 4.0 Era

Advanced sensors are becoming essential for modern factories, as they contribute by gathering comprehensive data about machines, processes, and human-machine interaction. They play an important role in improving manufacturing performance, in-factory logistics, predictive maintenance, supply chains, and digitalization in general. Wireless sensors and wireless sensor networks (WSNs) provide, in this context, significant advantages as they are flexible and easily deployable. They have reduced installation and maintenance costs and contributed by reducing cables and preinstalled infrastructure, leading to improved reliability. WSNs can be retrofitted in machines to provide direct information from inside the processes. Recent developments have revealed exciting possibilities to enhance energy harvesting (EH) and wireless energy transmission, enabling a reliable use of wireless sensors in smart factories. This review provides an overview of the potential of energy aware WSNs for industrial applications and shows relevant techniques for realizing a sustainable energy supply based on energy harvesting and energy transfer. The focus is on high-performance converter solutions and improvement of frequency, bandwidth, hybridization of the converters, and the newest trends towards flexible converters. We report on possibilities to reduce the energy consumption in wireless communication on the node level and on the network level, enabling boosting network efficiency and operability. Based on the existing technologies, energy aware WSNs can nowadays be realized for many applications in smart factories. It can be expected that they will play a great role in the future as an enabler for digitalization in this decisive economic sector.

The Impact of Applying Lean Manufacturing Fundamentals on the Improvement of Manufacturing Performance: A Case Study at the Yemeni National Company for Sponge and Plastic Industry

The study aimed at investigating the impact of applying lean manufacturing fundamentals on the improvement of manufacturing performance at the Yemeni National Company for Sponge and Plastic Industry (NCSPI). The study adopted the descriptive and analytical approach by using the case study method. A questionnaire was used for collecting data. After analyzing the data, the study findings revealed that there was a significant positive effect for the application of the lean manufacturing fundamentals on improving the manufacturing Performance in the Yemeni National Company for Sponge and Plastic Industry. The fundamentals were ranked in this order: cellular manufacturing; continuous improvement; automatic detection of a defect; and workplace organization. The study recommended that the Yemeni National Company for Sponge and Plastic Industry should give more care to achieve the integration of all Fundamentals of Lean manufacturing for a direct and effective impact on Manufacturing Performance Improvement.

Analytical evaluation of TPM performance based on an economic criterion

PurposeTotal productive maintenance (TPM) has been widely recognized as a strategic weapon for improving manufacturing performance. Evaluate efficiency of TPM implementation is considered as a key element in order to motivate staff and to give decision-makers more confidence.Design/methodology/approachThis study consists in developing a new method of evaluating TPM implementation, relying on analytical models and considering two preventive maintenance strategies: periodic and age-dependent.FindingsThe preventive maintenance period and TPM period defined as decision variables are obtained simultaneously by maximizing the expected profit under TPM implementation. A numerical example is presented and a sensitivity study is developed to validate the proposed models.Originality/valueThe aim of this research is to quantify, through analytic development, the impact of TPM implementation in a company by calculating and comparing the profit made with and without TPM.

The effect of equipment management capability maturity on manufacturing performance

Equipment management capability is crucial to the transformation and upgrading of manufacturing enterprises. Past studies ignore its significance and have not assessed manufacturing performance from the perspective of capability maturity yet and still want evidence from empirical test. For addressing this research gap, we combine research methods of qualitative and quantitative to define equipment management capability for exploring and verifying the relationship between equipment management capability maturity and manufacturing performance. Results of this study from 136 valid questionnaires indicate that capabilities of strategy, personnel and IT infrastructure have direct positive effects on manufacturing performance. Among them, equipment management strategy takes organisational & process and IT infrastructure as mediating variables, which have indirect positive influence on manufacturing performance. Meanwhile, organisational & process takes IT infrastructure as mediating variable which has indirect positive influence on manufacturing performance. Our work opens the black box of equipment management capability system and provides theoretical guidance for improving manufacturing performance.

KNOWLEDGE MANAGEMENT, ORGANIZATIONAL AMBIDEXTERITY, AND MANUFACTURING PERFORMANCE IN THE ERA OF INDUSTRY 4.0: A PROPOSED MODEL

Fourth Industrial Revolution (IR4.0) is changing the landscape of global manufacturing. As a developing nation, Malaysia’s manufacturing sector is a leading contributor to the nation’s GDP but its growth is in declining mode recently. Facing competition from countries with lower labour cost, Malaysia needs alternative ways to achieve competitive advantage. Many of its manufacturers are new to IR4.0 and also cautious of investing in such technologies to increase its manufacturing performance. Realizing this, Malaysia’s government introduced a policy on IR4.0 by focusing on the people, process and technology. The goal is to increase the skill set of the existing workforce through knowledge enhancement and adoption of advance manufacturing technologies. However, high level of transformation is needed, collaboration with external parties is important, and internal business processes and operating models need to change too. Many of them are lack in slack resources to pursue both explorative and exploitative learning. Organizational ambidexterity, which is the ability of a firm to manage both of these activities is crucial for proper knowledge management and improving manufacturing performance. The objective of this paper is to examine such interconnection from the context of a developing country as information from extant literature is scarce, especially on the balanced approach to source, transfer and protect the knowledge for optimum gain in manufacturing performance. Three main activities of knowledge management will be examined namely external knowledge sourcing, knowledge mobility and knowledge protection. The inclusive of knowledge protection also narrow the literature gap as it tends to be left out in previous studies due to its conflicting nature with other knowledge management activities. All the hypotheses and resulted conceptual model will be grounded with theories of Resource-Based view (RBV), Knowledge-Based View (KBV), Dynamic Capabilities and OA.

KNOWLEDGE MANAGEMENT, ORGANIZATIONAL AMBIDEXTERITY, AND MANUFACTURING PERFORMANCE IN THE ERA OF INDUSTRY 4.0: A PROPOSED MODEL

Fourth Industrial Revolution (IR4.0) is changing the landscape of global manufacturing. As a developing nation, Malaysia’s manufacturing sector is a leading contributor to the nation’s GDP but its growth is in declining mode recently. Facing competition from countries with lower labour cost, Malaysia needs alternative ways to achieve competitive advantage. Many of its manufacturers are new to IR4.0 and also cautious of investing in such technologies to increase its manufacturing performance. Realizing this, Malaysia’s government introduced a policy on IR4.0 by focusing on the people, process and technology. The goal is to increase the skill set of the existing workforce through knowledge enhancement and adoption of advance manufacturing technologies. However, high level of transformation is needed, collaboration with external parties is important, and internal business processes and operating models need to change too. Many of them are lack in slack resources to pursue both explorative and exploitative learning. Organizational ambidexterity, which is the ability of a firm to manage both of these activities is crucial for proper knowledge management and improving manufacturing performance. The objective of this paper is to examine such interconnection from the context of a developing country as information from extant literature is scarce, especially on the balanced approach to source, transfer and protect the knowledge for optimum gain in manufacturing performance. Three main activities of knowledge management will be examined namely external knowledge sourcing, knowledge mobility and knowledge protection. The inclusive of knowledge protection also narrow the literature gap as it tends to be left out in previous studies due to its conflicting nature with other knowledge management activities. All the hypotheses and resulted conceptual model will be grounded with theories of Resource-Based view (RBV), Knowledge-Based View (KBV), Dynamic Capabilities and OA.

KNOWLEDGE MANAGEMENT, ORGANIZATIONAL AMBIDEXTERITY, AND MANUFACTURING PERFORMANCE IN THE ERA OF INDUSTRY 4.0: A PROPOSED MODEL

Fourth Industrial Revolution (IR4.0) is changing the landscape of global manufacturing. As a developing nation, Malaysia’s manufacturing sector is a leading contributor to the nation’s GDP but its growth is in declining mode recently. Facing competition from countries with lower labour cost, Malaysia needs alternative ways to achieve competitive advantage. Many of its manufacturers are new to IR4.0 and also cautious of investing in such technologies to increase its manufacturing performance. Realizing this, Malaysia’s government introduced a policy on IR4.0 by focusing on the people, process and technology. The goal is to increase the skill set of the existing workforce through knowledge enhancement and adoption of advance manufacturing technologies. However, high level of transformation is needed, collaboration with external parties is important, and internal business processes and operating models need to change too. Many of them are lack in slack resources to pursue both explorative and exploitative learning. Organizational ambidexterity, which is the ability of a firm to manage both of these activities is crucial for proper knowledge management and improving manufacturing performance. The objective of this paper is to examine such interconnection from the context of a developing country as information from extant literature is scarce, especially on the balanced approach to source, transfer and protect the knowledge for optimum gain in manufacturing performance. Three main activities of knowledge management will be examined namely external knowledge sourcing, knowledge mobility and knowledge protection. The inclusive of knowledge protection also narrow the literature gap as it tends to be left out in previous studies due to its conflicting nature with other knowledge management activities. All the hypotheses and resulted conceptual model will be grounded with theories of Resource-Based view (RBV), Knowledge-Based View (KBV), Dynamic Capabilities and OA.

KNOWLEDGE MANAGEMENT, ORGANIZATIONAL AMBIDEXTERITY, AND MANUFACTURING PERFORMANCE IN THE ERA OF INDUSTRY 4.0: A PROPOSED MODEL

Fourth Industrial Revolution (IR4.0) is changing the landscape of global manufacturing. As a developing nation, Malaysia’s manufacturing sector is a leading contributor to the nation’s GDP but its growth is in declining mode recently. Facing competition from countries with lower labour cost, Malaysia needs alternative ways to achieve competitive advantage. Many of its manufacturers are new to IR4.0 and also cautious of investing in such technologies to increase its manufacturing performance. Realizing this, Malaysia’s government introduced a policy on IR4.0 by focusing on the people, process and technology. The goal is to increase the skill set of the existing workforce through knowledge enhancement and adoption of advance manufacturing technologies. However, high level of transformation is needed, collaboration with external parties is important, and internal business processes and operating models need to change too. Many of them are lack in slack resources to pursue both explorative and exploitative learning. Organizational ambidexterity, which is the ability of a firm to manage both of these activities is crucial for proper knowledge management and improving manufacturing performance. The objective of this paper is to examine such interconnection from the context of a developing country as information from extant literature is scarce, especially on the balanced approach to source, transfer and protect the knowledge for optimum gain in manufacturing performance. Three main activities of knowledge management will be examined namely external knowledge sourcing, knowledge mobility and knowledge protection. The inclusive of knowledge protection also narrow the literature gap as it tends to be left out in previous studies due to its conflicting nature with other knowledge management activities. All the hypotheses and resulted conceptual model will be grounded with theories of Resource-Based view (RBV), Knowledge-Based View (KBV), Dynamic Capabilities and OA.

Evaluation of TPM strategies for manufacturing performance improvement of Indian SMEs for strategic success

Indian small and medium enterprises (SMEs) are the heart of large organisations because every large organisation is purchasing a number of components from SMEs. In this study, the authors have made a qualitative model to find the preferred improvement strategy (TPM strategies) for implementing them in Indian SMEs by using an options field methodology (OFM), options profile methodology (OPM), analytic hierarchy process (AHP) and fuzzy set theory (FST). For this, first of all find various issues concerning improvement strategies and performance improvement through a questionnaire. OFM has converted these issues into options and then categorise them. The authors have identified four improvement strategies as profiles or a course of actions by using OPM. Pair wise comparison of AHP methodology is used to find the weight of various objectives of manufacturing performance improvement. Finally, FST is used to rank these four improvement strategies by making weighted position matrix and dominance matrix.