Apparel Manufacturing Industry Research Articles

Energy consumption modeling in industrial sewing operations: A case study on carbon footprint measurement in the apparel industry

In the textile supply chain, the apparel manufacturing industry heavily relies on energy consumption (EC), contributing to greenhouse gas emissions. Understanding and optimizing energy usage in apparel manufacturing is crucial for sustainable and energy-efficient manufacturing. The EC in the industrial sewing operations is directly linked with sewing parameters, including fabric seam length, standard sewing speed, and stitching time. In general, the carbon footprint of an apparel industry is measured by considering the standard minute value (SMV) and specific energy consumption (SEC). However, these metrics include non-productive time and do not accurately measure actual EC or assess the industry’s carbon footprint. To address these limitations, this case study tackles this technical issue by calculating the stitching time of an industrial sewing machine based on its actual EC derived from the sewing machine’s motor power. This study employs EC modeling for industrial sewing parameters, including fabric seam length, standard sewing speed, and stitching time. This proposed model utilizes real-time data collected during the garment-making process, including fabric spreading, cutting, sewing, and ironing. The study allocates eleven sewing machines for a specific garment style to stitch a basic knit fabric t-shirt. The total EC for the entire garment-making (t-shirt) process at a single line is 0.1052 kWh, equivalent to 59.97 g of CO2 emissions (Bangladesh’s CO2/kWh emission factor). This study explores that a direct-drive servo motor consumes approximately five times less than its maximum motor load power, making it more energy-efficient than other sewing machines. Therefore, this study demonstrates the effectiveness of EC modeling by incorporating industrial sewing parameters and selecting energy-efficient sewing machines to reduce carbon footprints and enhance environmental sustainability in the apparel manufacturing industry.

Exploring the barriers to implement industrial symbiosis in the apparel manufacturing industry: Implications for sustainable development

Industrial symbiosis, a promising approach for sustainable industrial practices, has garnered attention in recent days for its ability to enhance resource efficiency, minimize waste, and preserve the environment through collaborative exchanges among industries. In emerging economies like Bangladesh, integrating industrial symbiosis in the manufacturing industries offers the potential to balance economic growth with environmental sustainability. However, this integration encounters various barriers that complicate the implementation. Despite research on industrial symbiosis in robust economies, studies on emerging and developed economies are still scarce. To date, no research has yet investigated the barriers hindering the performance of industrial symbiosis in the Bangladeshi apparel manufacturing sector. To address this gap, this study integrates the Bayes theorem and the Best-Worst Method to identify and prioritize barriers to the Bangladeshi apparel manufacturing sector. From extensive literature reviews and expert validation, 17 barriers were identified. Findings reveal the “lack of technology and infrastructure readiness” as the most significant barrier, followed by “lack of inter-company cooperation” and “lack of management support”. Conquering these barriers empowers emerging economies to fortify the apparel manufacturing sector's resilience, resource efficiency, and environmental performance while fostering sustainable development via circular economy practices. This study is expected to guide policymakers and stakeholders in crafting targeted strategies for promoting steady growth and sustainable development in the apparel manufacturing sector of emerging economies like Bangladesh.

Management of products in the apparel manufacturing industry using DEMATEL-based analytical network process technique

Management of products in the apparel manufacturing industry using DEMATEL-based analytical network process technique

Design heuristics for cut order planning problems in the apparel industry

PurposeIn recent years, the demand for garments has significantly increased, requiring manufacturers to speed up their production to attract customers. Cut order planning (COP) is one of the most important processes in the apparel manufacturing industry. The appropriate stencil arrangement can reduce costs and fabric waste. The COP problem focuses on determining the size combination for a pattern, which is determined by the length of the cutting table, width, demand order, and height of the cutting equipment.Design/methodology/approachThis study proposes new heuristics: genetic algorithm (GA), symbiotic organism search, and divide-and-search-based Lite heuristic and a One-by-One (ObO) heuristic to address the COP problem. The objective of the COP problem is to determine the optimal combination of stencils to meet demand requirements and minimize the total fabric length.FindingsA comparison between our proposed heuristics and other simulated annealing and GA-based heuristics, and a hybrid approach (conventional algorithm + GA) was conducted to demonstrate the effectiveness and efficiency of the proposed heuristics. The test results show that the ObO heuristic can significantly improve the solution efficiency and find the near optimal solution for extreme demands.Originality/valueThis paper proposes a new heuristic, the One-by-One (ObO) heuristic, to solve the COP problem. The results show that the proposed approaches overcome the long operation time required to determine the fitting arrangement of stencils. In particular, our proposed ObO heuristic can significantly improve the solution efficiency, i.e. finding the near optimal solution for extreme demands within a very short time.

The Impact of Access to Intermediate Inputs on Export Margins: Firm-Level Evidence from the Regression Decomposition Approach

This paper analyzes how export margins responded to an intermediate input supply shock caused by the 2020 lockdown in China. We use regression decomposition with triple and quadruple difference-in-differences models to identify causal impacts and mitigate potential heterogeneity in transaction-level customs data from the Bangladesh apparel manufacturing industry. The triple difference estimate shows that the average export value per firm–product–destination combination declined by approximately 65%, leading to a decrease in overall exports of woven apparel from Bangladesh. The input supply shock also adversely affected the subgroups of firms across various firm-level characteristics along the intensive margin. Moreover, the export market share decomposition reveals that the shock significantly affected intensive margins by decreasing incumbents’ market allocation by 9%. An equivalent increase in extensive margins led to a readjustment in the market allocation, leading to fewer market leavers and slightly more new market entrants. Our results indicate that Bangladesh’s exports mostly decreased due to the smaller quantities of products exported rather than there being fewer firms, destinations, or products involved in export trade. There were significant market share reallocations that occurred after the Chinese input supply shock. An appropriate policy stance is required for sustainable export sector growth strategies, which will enhance the country’s defense against potential future shocks and foster the achievement of sustainable development goals (SDGs) in Bangladesh.

A grey approach to assess the challenges to adopting sustainable production practices in the apparel manufacturing industry: Implications for sustainability

The apparel manufacturing industry (AMI) significantly contributes to the economic growth of various developing nations. However, unsustainable production practices remain a major concern in this sector. Therefore, this study investigated the most significant challenges to adopting sustainable production practices in the apparel manufacturing sector from the perspective of an emerging economy like Bangladesh. Initially, the study identified the significant challenges through an extensive literature review and expert validation. Later, by utilizing a Grey Decision-Making Trial and Evaluation Laboratory (Grey DEMATEL) framework, the challenges were analyzed, and the interrelations among them were explored. The findings revealed that the ‘slow return on investment’, ‘lack of proper waste management systems’, and ‘reluctance to adopt advanced manufacturing processes’ are the top most significant challenges to adopting sustainable production practices in the apparel manufacturing sector. A sensitivity assessment was also performed to appraise the robustness of the obtained result. The outcomes of this research are expected to assist managers and practitioners in the AMI and other relevant industrial sectors in strategic planning to achieve various sustainable development goals (SDGs).

Examining the relationship between firm characteristics and Industry 4.0 technology adoption in Vietnam's apparel industry

ABSTRACT This study investigates the relationships between firm characteristics (region, firm size, firm age, and product category) and Industry 4.0 technology adoption in the Vietnamese apparel manufacturing industry. As the key Industry 4.0 technologies, Artificial Intelligence (AI), Interactive Robotics, Smart Sensors, Big Data, 3D Printing, physical Cyber-Physical Systems (CPS), and human-robot interaction were included to examine technology adoption. The hypotheses were tested using a series of Chi-square analyses with data gathered from 210 Vietnamese apparel-manufacturing firms. The results indicate no clear pattern of associations between firm characteristics and technology adoption and provide empirical support for firms’ strategic adoption of a certain set of Industry 4.0 technologies in line with their firm characteristics. On the other hand, the findings from scatter charts indicated that AI, Interactive Robotics, and 3D Printing are three key technologies that apparel firms applied the most and at a similar level.

Improving Quality, Productivity, and Cost Aspects of a Sewing Line of Apparel Industry Using TQM Approach

Total quality management (TQM) is a methodical strategy to minimize defects through six processes including choosing the manufacturer, gathering information, identifying the issues, analyzing the current situation, and coming up with solutions, putting the plan into action, data collection, and result analysis. The study investigates how quality, productivity, and cost aspects of a sewing line can be improved by implementing (TQM) approach in an apparel manufacturing industry in Bangladesh. This research concentrates on reducing four primary types of faults in the sewing department of DMC Apparels Ltd., such as uncut thread, up-down, broken stitch, and joint stitch. Proper information on several stitching errors was provided by the operators and helpers and those are used to assess the study in the next step. Performing the Pareto analysis and histograms to identify the primary concerns are part of the analyzing process. Moreover, using the 10 TQM pillars, the implementation step entails establishing the TQM mindset in the sewing line of the apparel industry. Several data-gathering methods are utilized to analyze primary data throughout the study’s final phase. To analyze the acquired data, Microsoft Excel was employed. The percentage of defect per hundred unit was decreased by 1.51% after optimization, as the recommended solutions’ impact on the defect level in the section was found to be quite significant. Significant parameters such as efficiency, quality, and cost aspect were analyzed and showed positive changes after implementing the TQM approach. The new technical layout also allows for the saving of five employees and a 3,000-min labor expense reduction. Finally, the research was completed by analyzing the basic pitch time graph and calculating the overall equipment effectiveness.

Analysis of the fire risks and mitigation approaches in the apparel manufacturing industry: Implications toward operational safety and sustainability

Fire risks pose a substantial threat to the apparel manufacturing industry since they can lead to immense property damage, potential loss of life, disruption of business operations, and reputational damage. In an emerging economy like Bangladesh, fire-related hazards are crucial due to the numerous deadly industrial fire incidents in recent years. This research, thereby, proposes an integrated multi-criteria decision-making (MCDM) framework to identify and mitigate fire risk hazards in the apparel manufacturing industry. Initially, the study identified 30 significant fire risk factors from the literature review. Then, after expert validation, an integrated Best Worst Method (BWM) and Weighted Sum Model (WSM) framework was utilized to prioritize the fire risk factors. Twenty-three mitigation actions were proposed afterward for the top-ranked risk factors based on National Fire Protection Association (NFPA) codes. An Interpretive Structural Modeling (ISM) with a Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis was later used to explore the interrelationships and dependencies among the mitigation actions. The ranking obtained from the BWM-WSM assessment revealed ‘combustible storage unseparated by fire-rated construction,’ ‘non-standard inspection, testing, and maintenance’, and ‘inadequate means of egress for the occupant load’ as the three most critical fire risk factors. The ISM-MICMAC analysis revealed ‘fire-rated construction’ and ‘standardized detection and protection’ as the most-driving mitigation actions. The study outcomes are expected to aid the managers and policymakers in emerging economies in formulating sustainable fire risk management strategies for the apparel industry and thus improve the operational safety and resilience of the sector.

DRIVING SUPPLY CHAIN FINANCE ADOPTION: EXPLORING THE INTERPLAY OF INNOVATION CAPABILITIES AND MARKET RESPONSE

The potential for enhanced performance within the textile and apparel sector has the capacity to bolster the competitiveness of Indonesia's industry. This study examines the impact of innovation capability and market responsiveness on the adoption of supply chain financing through supply chain integration in the textile and apparel manufacturing sector in Indonesia. A sample of one hundred thirty-five managers from textile and apparel manufacturing companies was selected using random sampling methodology. Subsequently, the collected data was subjected to analysis using SmartPLS 3.0 software. The empirical findings suggest a positive relationship between the ability to innovate and the ability to respond to market dynamics, and the likelihood of adopting supply chain financing. The research findings has the capability to provide significant insights to managers operating within the textile and apparel manufacturing industry in Indonesia, so helping them to improve business performance and strengthen their competitive advantage.

Development of Sustainability Balanced Scorecard: A Case Study from Apparel Industry Sri Lanka

Abstract This study aims to determine the obstacles the Sri Lankan apparel manufacturing industry faces when implementing sustainable practices and develop a Sustainability Balanced Scorecard to address those obstacles. The apparel export industry is one of Sri Lanka’s most significant contributors to the country’s overall economy. The multiple case study method was employed in conjunction with a qualitative approach in this study. This study also used data triangulation, which comprised both primary and secondary data from interviews and observations. Secondary information was gathered from annual reports and other documents. The population of this study is the apparel export industry and selected three apparel companies as the sample and interviewed nine managers from these companies. The interviewed data were transcribed into the transcript and analyzed through narrative analysis. By considering all the practices in three companies, this research constructed a sustainability balanced scorecard which can be used for other companies to build up their sustainability practices. The main issues identified in this research can be summarized as follows, Manual system of data entering and performance evaluation, there is no sufficient Hazardous Waste Management and disposal facilities in the country, Financial constraints prevent best-in-class equipment and procedures from being implemented. Sri Lanka has no solid waste recycling facilities for its primary waste type, fabric waste. As a final point, this research can be concluded that the regulators and policymakers can use the constructed sustainability balanced scorecard for the policy development on sustainability practices.

A digital twin framework development for apparel manufacturing industry

The apparel manufacturing industry faces challenges due to fast-changing fashion trends, increased product variety, and personalized demands. Quick and optimized decision-making is crucial to overcome these barriers. This study aims to develop a methodology for applying Digital Twin (DT) technology in apparel manufacturing plants. We demonstrate the applicability and exhibit efficacy of the proposed method by presenting a case study on implementing the DT technology at a sewing assembly line. The proposed approach provides step-by-step guidance, collecting real-time data and conducting dynamic simulations to reduce bottleneck operations. DT technology assists in decision-making, enabling apparel manufacturing plants to respond quickly to changing demands and to reduce bottleneck operations. This study demonstrates the effectiveness of the proposed methodology by reducing downtime and improving production efficiency. The proposed method can improve production efficiency, reduce downtime, and respond quickly to changing demands in the apparel manufacturing industry.

Evaluating barriers to sustainable boiler operation in the apparel manufacturing industry: Implications for mitigating operational hazards in the emerging economies.

The efficiency with which conventional boilers perform, in terms of sustainability, is affected by a variety of factors. Unsustainable boiler operating practices are still surprisingly frequent in developing countries, resulting in environmental liabilities and catastrophic accidents. It is a serious problem in developing countries like Bangladesh, where boilers are utilized extensively in the apparel manufacturing sector. However, no research has yet examined the challenges or barriers associated with sustainable boiler operation in the apparel manufacturing sector. This study, thereby, utilizes an integrated MCDM approach, combining the fuzzy theory and the decision-making trial and evaluation laboratory (DEMATEL) method, to identify, prioritize, and explore the relations among the barriers to sustainable boiler operation in the apparel manufacturing industry, from an emerging economy perspective. The barriers were initially identified from the literature and a visual survey of 127 factories. After expert validation, thirteen barriers were finally selected to be analyzed utilizing the fuzzy DEMATEL method. The study findings revealed that 'Absence of water treatment facilities', 'Fossil fuel burning and GHG emissions', and 'Excessive consumption of groundwater' are the three most prominent barriers to sustainable boiler operation. The cause-effect relations among the barriers suggest that 'Inadequate compliance with safety and hazard regulations' is the most influential and 'Fossil fuel burning and GHG emissions' is the most influenced barrier. This study is expected to guide the managers and policymakers of the apparel manufacturing sector in successfully overcoming the barriers to sustainable boiler operation, thus mitigating the operational hazards and achieving the sustainable development goals (SDGs).

Analyzing the critical success factors to implement green supply chain management in the apparel manufacturing industry: Implications for sustainable development goals in the emerging economies

Green supply chain management (GSCM) is an emerging concept of modern supply chain management (SCM) that integrates eco-friendly and ethical environmental concerns with the traditional supply chain by reducing the negative impacts of unsustainable manufacturing practices. Developed countries have already adopted different sustainable SCM practices. However, despite being one of the significant sources of export earnings in emerging economies like Bangladesh, the apparel manufacturing industry is still lagging in the case of GSCM implementation. This study, thereby, utilized an integrated multi-criteria decision-making (MCDM) approach, including gray theory and decision-making trial and evaluation laboratory (DEMATEL) method to identify, prioritize, and examine the relations among the critical success factors (CSFs) to implement GSCM practices in the Bangladeshi apparel manufacturing industry. The study initially identified the CSFs from the literature review. After expert validation, sixteen significant CSFs were finally analyzed by the gray-DEMATEL method. The findings revealed that 'demand from buyers', 'economic and tax benefits', and 'government rules and regulations' are the three most prominent CSFs to implement GSCM practices in the apparel manufacturing industry. The cause-effect relations among the CSFs were later explored, which indicated 'Economic and tax benefits' to be the most influencing and 'Supplier training and cooperation' to be the most influenced CSF. The study insights can potentially guide apparel industry managers in successfully implementing GSCM practices toward achieving long-term sustainability and sustainable development goals (SDGs).

Editorial Impacts of Technology Management on the Apparel Retailing and Manufacturing Industry

Editorial Impacts of Technology Management on the Apparel Retailing and Manufacturing Industry

Drivers for Sustainable Supply Chain Management and the Practices in Ethiopian Apparel Industries

Environmental, social, and economic concerns in the apparel manufacturing industries have grown in recent years. The sustainability of the apparel supply chain management in developing countries is characterized by operations highly hazardous to the environment and unethical to society and of important economic value. Studies showed that socioeconomic and cultural differences in different countries affect the success of sustainability practices. Therefore, extensive research is required to measure the current challenges of sustainable practices from environmental, social, and economic perspectives of the apparel industry. Due to unsustainable practices, competitiveness in export and local markets is low in the Ethiopian apparel industries. This paper explores the effect of different factors on the sustainable practices of Ethiopian apparel manufacturing industries. A conceptual framework was formulated to measure sustainable practices. Questionnaires, interviews, and secondary data sources were used for data collection. The data are prepared and pretested for reliability. Integrated interpretive structural modelling and structural equation modelling techniques have been employed for model building and data analyses to see the relationship between the challenges and the existing practices. The proposed model was validated using partial least squares structural equation modelling. The Bootstrapping technique in smart partial least square ensures the reliability of the data for small sample size. The result showed a significant relationship between the factors and sustainable practices. All the environmental, economic, and social perspectives were statistically tested and found significant atpvalues of 0.05. Sustainable practice in the apparel manufacturing supply chain was found to be low with a mean value of three. This performance is far below the average standard in developing and developed countries. This research provides customized areas of intervention from environmental and social aspects that recognize the societal difference towards sustainability awareness and motivation to implement sustainability initiatives in Ethiopian apparel manufacturing industries. This research could provide awareness for business owners and policymakers and help understand the limitations of existing sustainability practices and the need for interventions. Therefore, apparel manufacturing industries could be potential sourcing destinations for global apparel manufacturing industries.

Unveiling the critical drivers of purchasing and supply management in apparel manufacturing industry

In a multibillion-dollar industry employing millions, the role of purchasing and supply management (PSM) is often underestimated despite its pivotal contribution. This study addresses the pressing need to understand and optimize PSM in the context of the apparel manufacturing industry. The objectives are to identify key factors influencing PSM and provide industry stakeholders with a strategic roadmap for improvement.

Impact of Green Procurement on Purchasing Performance (Special reference to the Apparel Manufacturing Industry in Sri Lanka)

This study will explore the impact of green procurement on purchasing by special reference to the ap-parel manufacturing industry in Sri Lanka. In order to achieve the stated purpose, the researcher devel-oped three research questions, three research objectives, and three hypotheses. Based on institutional theory and natural resource-based view theory, this study constructs a theoretical framework to clarify the mechanisms underlying the relationship between variables. Utilizing a sample of two hundred and fifty-two Sri Lankan professionals from the large-scaled apparel manufacturing sector, a structural model is outlined and tested using structural equation modeling (SEM). The study results demonstrate that green procurement has a positive and significant impact on purchasing performance. Further, the survey result recommended that the relationship between product-based green procurement and pro-cess-based green procurement on purchasing performance was positive and statistically signifi-cant. Consequently, organizations striving to achieve better purchasing performance should focus more on executing green procurement practices. These two kinds of procurement capabilities present two facets of a firm’s practice on green procurement, which complements rather than substitutes each other. The measurements developed in this study can capture the different aspects of purchasing perfor-mance, thus not only enabling use by practitioners to identify the immediate outcomes of it but also to understand its impacts on organizational performance.

Impact of Green Procurement on Purchasing Performance: With Special Reference to the Apparel Manufacturing Industry in Sri Lanka

Impact of Green Procurement on Purchasing Performance: With Special Reference to the Apparel Manufacturing Industry in Sri Lanka

Textile-apparel manufacturing and material waste management in the circular economy: A conceptual model to achieve sustainable development goal (SDG) 12 for Bangladesh

The textiles and apparel manufacturing industry in the upstream fashion supply chain generates substantial materials waste that requires urgent efforts to manage effectively, reduce environmental impact, and foster sustainable practices. A huge research scope lies in materials waste management of upstream textiles and apparel manufacturing within the scopes of circular economy to achieve Sustainable Development Goal (SDG) 12 for Bangladesh. This research identifies and categorises the materials waste generated in various production stages, determines the economic loss, and traces the informal trading of waste materials. Following an exploratory multiple-case approach, this research collects data from 17 textiles and apparel factories through semi-structured questionnaires, followed by materials stream mapping and observations. The study estimates a loss of approximately 0.70 USD for every piece of apparel export. To trace the destination of waste, it has been found that approximately 15 tons of informal trading of wastes took place in a single underground market. Overall, it leads to a significant loss of value addition that could have been added through a circular economy. Finally, to help achieve SDG 12, this study develops a conceptual waste management model in upstream textiles and apparel manufacturing with potential application opportunities within the circular economy. • Materials stream mapping is conducted in the textile-apparel production chain. • Approximately 0.70 USD is lost for every piece of apparel export. • Traceability of textile wastes and scope of circularity is discussed. • A circular economy-led conceptual model is proposed to achieve SDG 12 in Bangladesh.