Lead Time Reduction Research Articles

Scheduling for additive manufacturing with two-dimensional packing and incompatible items

Additive manufacturing technology can enable low-cost, efficient production of low-demand, highly-complex customized items with reduced lead time if production is judiciously planned. This paper addresses the assignment of requested items into batches and the scheduling of the batches onto 3D printers. The objective is to minimize the manufacturing makespan while satisfying items’ compatibility, two-dimensional no-overlap and containment packing constraints within a batch, and machine’s capability to manufacture a batch. The problem is modeled as a mixed integer linear program (MIP) that solves instances up to 100 items. For hard and large instances, this paper proposes a matheuristic that fathoms packings using a step-wise check procedure. Computational results reveal that the proposed heuristic improves the makespan of MIP solutions of hard instances by 12% on average, with improvements reaching up to 72% for instances with 150 items. They further show that the proposed heuristic finds the best makespan for 88% of all cases. Finally, we provide useful managerial insights for production flexibility and scheduling policies.

Evaluating the Impact of ERP Implementation on Supply Chain Performance: A Case Study of Youngs Food in Pakistan

This study investigated the impact of Enterprise Resource Planning (ERP) implementation on supply chain performance at Youngs Food, a leading FMCG company in Pakistan. Utilizing a quantitative research methodology, the study aimed to assess how ERP systems influence various aspects of supply chain management, including process automation, lead time reduction, cost reduction, and delivery improvement. Data were collected from employees involved in the ERP transformation process through a structured questionnaire. The findings revealed that ERP implementation significantly enhances supply chain performance. Specifically, process automation emerged as the most influential factor, followed by cost reduction, improved deliveries, and lead time reduction. The study confirmed that ERP systems streamline operations, reduce operational costs, and improve efficiency and customer satisfaction. The comprehensive analysis underscores the critical role of ERP systems in modern supply chain management, advocating for their strategic adoption to achieve competitive advantage and operational excellence.

Optimizing supply chain management: strategic business models and solutions using SAP S/4HANA

In today's highly competitive and rapidly evolving business environment, optimizing supply chain management (SCM) has become a critical imperative for organizations aiming to enhance operational efficiency, reduce costs, and improve customer satisfaction. SAP S/4HANA, a next-generation enterprise resource planning (ERP) suite, offers a comprehensive and integrated platform for streamlining and modernizing SCM processes. This review explores the strategic business models and solutions facilitated by SAP S/4HANA, focusing on its impact on various facets of supply chain operations, including procurement, manufacturing, logistics, and inventory management. The implementation of SAP S/4HANA enables organizations to leverage advanced analytics, real-time data processing, and intelligent automation to optimize supply chain functions. By providing a unified view of supply chain activities, SAP S/4HANA enhances visibility, enabling proactive decision-making and fostering a more responsive and agile supply chain. Key features such as predictive analytics and machine learning algorithms facilitate demand forecasting and inventory optimization, reducing the risk of stockouts and overstock situations. Furthermore, SAP S/4HANA supports the integration of Internet of Things (IoT) technologies, allowing for real-time monitoring of assets and operations. This connectivity enhances the ability to manage logistics and transportation more efficiently, reducing lead times and improving delivery performance. The platform's ability to harmonize data from various sources also aids in supplier collaboration, ensuring better alignment with suppliers' capabilities and enhancing the overall supply chain resilience. Strategic business models enabled by SAP S/4HANA include just-in-time (JIT) production, which minimizes inventory costs, and demand-driven replenishment, which aligns production schedules with actual customer demand. Additionally, the adoption of digital twin technology within SAP S/4HANA allows for virtual modeling and simulation of supply chain scenarios, facilitating strategic planning and risk management. In conclusion, SAP S/4HANA provides a robust foundation for optimizing supply chain management through its advanced technological capabilities and integrated approach. Organizations adopting SAP S/4HANA can achieve significant improvements in supply chain efficiency, agility, and resilience, positioning themselves for sustained competitive advantage in the dynamic global market. This exploration highlights the transformative potential of SAP S/4HANA in redefining supply chain strategies and operational excellence.

Shortening The Last-Mile: Impact of Zipline Medical Drone Delivery on The Operations of Hard-to-Reach Healthcare Facilities in Northern Ghana.

Purpose: This research study investigated the impact of Zipline Medical Drone Delivery on the operations of last-mile healthcare facilities in northern Ghana. Design/Methodology/Approach: The research study adopted an exploratory research design to determine the impact of Zipline’s medical drone delivery on the operations of last-mile healthcare facilities in Northern Ghana. An online survey questionnaire was deployed to collect quantitative data from 159 trained employees of last-mile health facilities who were selected through a purposive sampling technique from last-mile drone-served healthcare facilities. Findings: The study established that drone delivery speed, logistics efficiency and availability of drone delivery resources significantly impacted zipline delivery of medical commodities to last-mile public healthcare facilities in Northern Ghana, reducing commodity delivery lead-time and improving access to essential healthcare supplies for efficient service delivery. Research Limitation/Implications: This research focused mainly on the impact of drone delivery of medical commodities on the operations of last-mile public healthcare facilities in Northern Ghana. Practical Implications: The results of this study show that by enhancing drone delivery speed, logistics efficiency and drone resource availability, the operations of public healthcare facilities can be improved by ensuring that essential medicines are made available, patient waiting time is significantly reduced and outpatient services are improved. Social Implication: The study recommends the establishment of a Zipline-Administrators partnership which will eventually result in a reduction of medical commodity lead-time, improved accessibility of patients to essential health commodity supplies and general cost savings to the community. Originality/Value/Novelty: Although drone technology has been the subject of numerous studies in Ghana, none has investigated the impact of medical commodity drone delivery services on the operations of last-mile healthcare facilities in Northern Ghana. This study therefore explored the impact of drone delivery services from the last-mile healthcare facilities’ perspective.

Multi-Agent Simulation Approach for Modular Integrated Construction Supply Chain

The shift from traditional on-site to off-site construction marks a significant evolution in the construction industry, characterized by increasing levels of prefabrication. These advancements enhance construction efficiency, reduce lead times, and mitigate environmental impacts, leading to modular integrated construction (MiC). However, MiC presents complex supply chain challenges, particularly in the transportation of prefabricated components and fully integrated modules. This study addresses these challenges by employing a multi-agent simulation using AnyLogic to optimize MiC transport logistics. The simulation models the interactions of various agents involved in the MiC process to improve operational efficiency and reduce costs. Results demonstrate that using three vehicles per supplier minimizes total transport costs, effectively balancing fixed and variable expenses while eliminating penalties for project delays. The findings highlight the cost efficiency of MiC, showing potential savings due to centralized assembly and optimized logistics. These significantly reduce material transportation and related costs, contributing to the overall efficiency and sustainability of construction projects. These insights underscore the value of multi-agent simulation in addressing the complexities of MiC supply chains.

Design complexity based flexible order dispatching for additive manufacturing production

Understanding design complexity for additive manufacturing (AM) is essential in AM production planning since conventional make-to-order production for individual AM orders of complex designs can amplify operational uncertainty in an entire AM production system. As a response, this study aims not only to demonstrate the impact of design complexity on AM production but also to propose a novel order dispatching approach based on design complexity that mitigates operational uncertainty in an AM production system. First, a design complexity measure was developed using an information theoretic approach. Next, a discrete-event simulation model to represent an AM production system consisting of parallel AM machines for jet-engine bracket designs was built to identify the impact of design complexity on average order lead time and total production cost through regressions. Finally, a flexible order dispatching rule that reflects operational attitudes toward design complexity was proposed to determine part-processing priorities by tracking both part- and system-level design complexity states in a centralized queue for AM production. The proposed dispatching rule was compared with relevant static dispatching rules to assess its performance in operational efficiency under varied attitudes toward design complexity. The findings from this study clearly showed the negative impact of design complexity on operational performance for AM production. Moreover, the proposed dispatching rule resulted in lead time reduction and balanced lead time performance in AM production against alternative static dispatching strategies. This study demonstrates the importance of design complexity-based flexible operations to properly handle latent uncertainties in an AM production system.

Inventory Management Optimization: Balancing Cost and Service Levels

Efficient management of inventory plays a role, in the success of businesses across sectors. Finding the equilibrium between keeping inventory costs low and meeting customer needs is a challenge that requires constant exploration and creativity. This study delves into the complexities of optimizing inventory management focusing on strategies that effectively handle the trade offs between minimizing expenses and fulfilling customer expectations. By delving into an analysis of existing literature this study consolidates approaches, models and best practices implemented by companies to enhance the efficiency of inventory management. It thoroughly examines aspects such as improving demand prediction accuracy reducing lead times optimizing safety stock levels and integrating supply chains. Additionally it explores how advanced technologies like intelligence data analytics and automation are transforming inventory management processes.Moreover this research delves into how industry landscapes, market dynamics and business goals influence inventory management tactics. Through real world examples and empirical data analysis it offers insights, on how organizations can tailor their strategies to meet needs while balancing the objectives of cost control and service level improvement. In the end this study adds to what we know about improving inventory management by providing advice and tips for companies to gain lasting edges in todays ever changing market. KEYWORDS: Research Paper, Blockchain, Management, Risk Evaluation, Empirical Analysis

Accuracy of Salivary Circulating Tumor Human Papillomavirus DNA in Detecting Oropharyngeal Cancer

Circulating tumor human papillomavirus DNA (ctHPV DNA) has shown potential as a biomarker capable of improving outcomes in patients with HPV-related oropharyngeal (OP) cancer. It can be isolated from plasma or saliva, with the latter offering reduced invasiveness and theoretic reduction of lead time. To perform a systematic review and meta-analysis on the accuracy of salivary ctHPV DNA for detecting HPV-associated OP cancer. Cochrane Library, Embase, PubMed, and Web of Science databases were searched from inception through October 2023. All patients who underwent salivary ctHPV DNA testing at presentation for possible or diagnosed HPV-related OP cancer were included. Non-English and review publications were excluded. Two authors independently voted on article inclusion with a third resolving conflicting votes. Following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines, multiple authors independently abstracted data and assessed bias of included articles. Bivariate random-effects meta-analysis was performed with I2 to assess for study heterogeneity. Sensitivities, specificities, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratios (DOR) with 95% CIs alongside area under the curve (AUC) of a summary receiver operating characteristic (SROC) curve were calculated. The initial analysis took place throughout December 2023. Of 440 initially identified articles, 6 met inclusion criteria and demonstrated moderate heterogeneity (I2 = 36%) with low risk of bias and low applicability concerns. Overall, 263 total patients were included with a median (range) age of 58 (39-86) years, and 228 (87%) were male patients. Per updated prognostic staging criteria, localized tumors (ie, stages 1 or 2) comprised most cancers at 139 (77%), whereas advanced ones (ie, stages 3 or 4) comprised the remaining 41 (23%). Pooled sensitivity, specificity, PLR, NLR, and DOR values were 64% (95% CI, 36%-85%), 89% (95% CI, 46%-99%), 11.70 (95% CI, 0.37-77.00), 1.21 (95% CI, 0.08-7.00), and 139.00 (95% CI, 0.05-837.00), respectively. The AUC of the SROC curve was 0.80. This study supports salivary ctHPV DNA as an acceptably specific test in detecting HPV-associated OP cancer that would benefit from testing in clinical trials prior to real-time implementation.

Integrated operations planning model for the automotive wiring industry

An integrated operations planning model for automotive wiring companies is studied to improve synchronization between production activities and inventory flows. These combined factors are growing in significance as they drive the need to take proactive steps in manufacturing and distributing wiring materials within the supply chain. This involves anticipating the requirements of different automotive manufacturers and thereby guaranteeing a consistent, uninterrupted, and punctual provision of raw wiring materials. This support is vital for sustaining the ongoing manufacturing operations in the automotive sector. For this push flow system, the proposed operational model is based on integer linear programming, considering capacity and bill of materials constraints to determine production quantities, inventory levels, and machine sizing. Real-life data from the automotive wiring industry validates the effectiveness of coordinated production and inventory activities, resulting in significant lead time reductions of up to 60 %. These findings provide compelling reasons for automotive wiring partners to engage in joint operations planning.

Enhancing manufacturing productivity: A review of AI-Driven supply chain management optimization and ERP systems integration

This abstract delves into the realm of manufacturing productivity enhancement through the review of AI-driven supply chain management (SCM) optimization and Enterprise Resource Planning (ERP) systems integration. As industries strive for operational excellence, the convergence of artificial intelligence (AI) and supply chain management emerges as a transformative force in driving efficiency, agility, and competitiveness. Through a comprehensive analysis, this abstract examines the synergistic relationship between AI-driven SCM optimization and the integration of ERP systems, elucidating their collective impact on manufacturing productivity. AI-driven SCM optimization encompasses a spectrum of technologies and methodologies, including predictive analytics, machine learning, and autonomous decision-making systems, aimed at optimizing various facets of the supply chain, from demand forecasting and inventory management to production planning and logistics optimization. By harnessing the power of AI, manufacturers can enhance forecasting accuracy, reduce lead times, optimize inventory levels, and mitigate supply chain disruptions, thereby improving overall productivity and customer satisfaction. Integration of ERP systems plays a complementary role in manufacturing productivity enhancement by providing a centralized platform for data management, process automation, and cross-functional collaboration. Through seamless integration with AI-driven SCM optimization tools, ERP systems enable real-time data exchange, actionable insights, and end-to-end visibility across the supply chain, facilitating informed decision-making and agile response to dynamic market conditions. Drawing insights from case studies and industry examples, this abstract highlights best practices, challenges, and emerging trends in AI-driven SCM optimization and ERP systems integration. Strategies for successful implementation, including organizational readiness assessment, change management, and stakeholder engagement, are discussed to guide manufacturers in unlocking the full potential of these transformative technologies. In conclusion, the convergence of AI-driven SCM optimization and ERP systems integration offers a compelling pathway for enhancing manufacturing productivity, driving operational excellence, and sustaining competitive advantage in the digital era.. Keywords: Artificial Intelligence, Supply Chain Management, Enterprise Resource Planning, Manufacturing Productivity, AI Integration, Predictive Analytics.

OPTIMIZING SUPPLY CHAIN EFFICIENCY IN THE MANUFACTURING SECTOR THROUGH AI-POWERED ANALYTICS

The integration of AI-powered analytics offers transformative potential in optimizing supply chains within the manufacturing sector. This study adopts a qualitative, case study methodology to explore the specific ways manufacturers utilize AI-powered solutions in areas such as demand forecasting, inventory management, logistics planning, and predictive maintenance. Findings indicate substantial gains in efficiency, cost savings, and improved supply chain resilience. Additionally, the study highlights how AI-driven optimizations lead to an enhanced customer experience through increased product availability, reduced lead times, and a more responsive supply chain. Through detailed analysis of real-world implementations, the study provides practical guidance for manufacturers seeking to leverage AI to transform their supply chain operations.

Supply Chain Performance in the Manufacturing Sector: The Role of Lead-Time Management Strategies

The objective of this research was to evaluate the effectiveness of lead-time management strategies in influencing the operational efficiency of manufacturing enterprises. While prior studies have recognized lead time as a crucial factor impacting supply chain performance, scant attention has been paid to the specific contribution of lead-time management strategies in this context. Hence, this study aimed to bridge this gap. By employing a descriptive survey research design, data were collected from a sample of 153 manufacturing firms selected through purposive sampling. The primary data collection instrument was a structured questionnaire, and statistical analyses were conducted using SPSS software. The findings indicate that early involvement of suppliers in product design and dissemination of accurate customer specifications significantly reduces lead time. Process automation and efficient transport management, including route planning and vehicle scheduling, were found to enhance supply chain performance. Consequently, the study concludes that early supplier involvement, process automation, and effective transport management positively impact supply chain performance. Based on these findings, it is recommended that manufacturing companies prioritize initiatives aimed at reducing lead time, such as minimizing waiting times, engaging suppliers early in the process, automating processes, and improving transport management in order to enhance overall supply chain performance.

Optimizing extreme manufacturing framework: a secure and efficient 3D printing integration framework

This study presents a comprehensive framework for extended manufacturing with integrated 3D printing technologies, exemplifying a paradigm shift in the manufacturing landscape. The Digital Thread Integration establishes a dynamic foundation, enabling real-time collaboration and data flow throughout the product lifecycle. Leveraging advanced AI-driven optimization, Digital Design Platforms streamline designs, processing 1,000 iterations per hour, and recommending materials based on component requirements. On-Demand Manufacturing Hubs strategically placed globally achieve substantial reductions in lead times (48 h) and material waste (15%). The Cybersecurity Infrastructure ensures the sanctity of the digital environment, employing secure communication protocols and an Intrusion Detection System (IDS) responding to threats in milliseconds. The Data Analytics Hub contributes to continual improvement by analysing 100 GB of 3D printing data daily, generating 50 actionable insights weekly. User Interface and Accessibility initiatives empower the workforce through intuitive training modules and responsive help desks. In conclusion, this framework exemplifies secure, efficient, and data-driven extended manufacturing, positioning the industry at the forefront of technological advancement.

Review on Additive Manufacturing Process in Aircraft Industries

This paper explores the feasibility of implementing 3D printing technology for manufacturing seat buckles in the Airbus A380. While additive manufacturing has gained attention for its versatility, safety-critical components require rigorous testing and certification. Through a comprehensive review of literature and expert interviews, this study analyzes the viability of 3D printing for seat buckle production. The results indicate that traditional manufacturing methods, such as injection molding and forging, remain the preferred choices due to their established reliability and quality control procedures. The aviation industry places the utmost importance on safety and reliability, especially in the manufacturing of safety-critical components like seat buckles. This paper examines the potential integration of 3D printing technology into the production process of seat buckles for the Airbus A380, considering the stringent certification requirements and performance expectations. A literature review encompassing additive manufacturing techniques, aerospace certification processes, and current seat buckle manufacturing practices was conducted. Expert interviews were also conducted to gather insights from industry professionals with expertise in aerospace manufacturing. The analysis revealed that conventional manufacturing methods such as injection molding and forging are currently preferred for seat buckle production in the Airbus A380 and other aircraft parts. These methods have established reliability and quality control procedures, ensuring compliance with rigorous safety standards. Although 3D printing has found success in prototyping and non-critical components, its application in safety-critical components like seat buckles is limited. The decision to favor traditional manufacturing methods for seat buckle production in the Airbus A380 is driven by the need for extensively tested and certified components. Safety-critical parts undergo stringent testing to guarantee their performance under various operating conditions. While 3D printing offers design flexibility and reduced lead times, further research and development is necessary to ensure its viability in safety-critical applications. At present, 3D printing technology is not widely employed for manufacturing seat buckles in the Airbus A380. Traditional methods provide the required reliability and quality control procedures. However, ongoing advancements in additive manufacturing may present future opportunities for incorporating 3D printing technology into safety-critical applications within the aerospace industry. Further research and development are necessary to explore these possibilities.

Design and Implementation of GaN-Based Two Switch Flyback With Synchronous Rectification for New Space Applications

This article presents a comprehensive investigation and implementation of a continuous conduction mode pulse width modulated two-switch DC/DC flyback converter utilizing Gallium Nitride Field Effect Transistors (GaNFETs) for New Space applications. The New Space concept advocates for the integration of Commercial Off-The-Shelf (COTS) materials in the space industry. The approach offers cost-effective solutions and reduces lead time for space designs. The study provides steady-state analysis and design considerations for two switch flyback converters, highlighting the transformative capabilities of GaNFETs, especially in high-frequency operations. The rationale behind the preference for GaNFETs over MOSFETs in satellite power supply applications and the strategic benefits of COTS materials are explained in detail. In addition, the synchronous rectification method is implemented to obtain better efficiency, particularly for high-output current operations. The converter achieves an efficiency of over 87% when the load exceeds 50%, with varying input voltages from 20 V to 40 V and a switching frequency of 300 kHz. The experimental findings show that the designed converter can serve as a high efficiency and reliable satellite power converter.

STRATEGIC OPERATIONS MANAGEMENT IN FMCG: A COMPREHENSIVE REVIEW OF BEST PRACTICES AND INNOVATIONS

Strategic operations management (SOM) in the fast-moving consumer goods (FMCG) industry plays a crucial role in driving efficiency, quality, and customer satisfaction. This paper presents a comprehensive review of best practices and innovations in SOM within the FMCG sector, aiming to provide insights into how companies can optimize their operations to achieve competitive advantage and sustainable growth. The review begins by examining the key challenges faced by FMCG companies, including demand volatility, short product life cycles, and complex supply chains. It then explores how strategic operations management practices can help address these challenges and improve overall performance. One of the key areas of focus in SOM for FMCG companies is inventory management. Best practices such as demand forecasting, lean inventory principles, and just-in-time (JIT) inventory systems are discussed, highlighting their importance in reducing stockouts, minimizing waste, and improving overall supply chain efficiency. Another critical aspect of SOM in the FMCG industry is production planning and scheduling. The review outlines how advanced planning tools, such as enterprise resource planning (ERP) systems and advanced analytics, can help FMCG companies optimize production processes, reduce lead times, and enhance flexibility to respond to changing market demands. Furthermore, the paper discusses the role of technology and innovation in enhancing SOM practices in the FMCG sector. It explores how technologies such as automation, artificial intelligence (AI), and the Internet of Things (IoT) are transforming FMCG operations, enabling companies to achieve higher levels of efficiency, quality, and sustainability. The review also highlights the importance of collaboration and partnerships in SOM for FMCG companies. It discusses how strategic alliances with suppliers, distributors, and other stakeholders can help FMCG companies optimize their supply chains, reduce costs, and improve customer satisfaction. Overall, this paper provides a comprehensive overview of best practices and innovations in strategic operations management for FMCG companies. It emphasizes the importance of adopting a holistic approach to SOM, integrating people, processes, and technology to achieve competitive advantage and sustainable growth in the dynamic FMCG industry. This review paper systematically examines existing literature on operations management within the FMCG sector, highlighting effective strategies for coordinating operations, crew scheduling, and logistics to uphold professionalism and achieve peak performance. It aims to aggregate insights on process improvement opportunities, conflict management techniques, and cross-functional team dynamics that have led to world-class customer experiences and increased product sales. The review will also discuss the role of technology in maintaining operational records and facilitating continuous improvement in FMCG logistics and supply chain management.
 Keywords: Innovations, Best Practices, SOM, FMCG, Comprehensive.

INNOVATIVE MATERIAL PROCESSING TECHNIQUES IN PRECISION MANUFACTURING: A REVIEW

Precision manufacturing plays a pivotal role in various industries, demanding high accuracy, efficiency, and quality in the production process. The continual pursuit of innovation in material processing techniques is essential to meet evolving demands and challenges. This review explores the latest advancements and innovations in material processing methods within precision manufacturing. The review encompasses a comprehensive analysis of various innovative material processing techniques, including additive manufacturing, subtractive manufacturing, and hybrid approaches. Additive manufacturing, often referred to as 3D printing, has gained significant attention for its capability to produce complex geometries with high precision. The exploration of novel materials, such as metal alloys, polymers, and composites, expands the applicability of additive manufacturing in diverse industrial sectors. Subtractive manufacturing techniques, such as milling, turning, and grinding, are also undergoing transformative advancements to enhance precision and efficiency. Emerging technologies like abrasive waterjet machining, electrical discharge machining (EDM), and laser machining offer improved accuracy and surface finish while enabling the processing of a wide range of materials, including hard-to-machine alloys and composites. Hybrid manufacturing approaches, combining additive and subtractive techniques, are revolutionizing precision manufacturing by leveraging the strengths of both methods. These hybrid systems enable the production of intricate components with high precision, reduced lead times, and minimized material waste, addressing the challenges of traditional manufacturing processes. Furthermore, the review highlights advancements in process monitoring and control technologies, such as in-process sensing, real-time feedback systems, and adaptive control algorithms, facilitating enhanced quality assurance and productivity in precision manufacturing. The integration of advanced computational tools, simulation techniques, and artificial intelligence further augments the optimization and customization capabilities of material processing techniques, driving efficiency and innovation in precision manufacturing. Overall, this review provides valuable insights into the latest developments and trends in innovative material processing techniques, offering a roadmap for future research directions and applications in precision manufacturing industries.
 Keywords: Material, Processing, Techniques, Precision, Manufacturing, Review.

IMPROVING EMPLOYEE AND WORKPLACE PERFORMANCE VIA LEAN MANUFACTURING PRACTICES: A CASE STUDY IN TEXTILE COMPANY

This study explores the possibility of enhancing employee and workplace performance by implementing lean manufacturing practises in a textile industry. It addresses the the limited availability of empirical data concerning lean practices, with a particular focus on the textile industry. Qualitative approaches were employed involving direct observations and in-depth interviews with important stakeholders, followed by a thematic analysis of the data. The findings highlight the effects of lean manufacturing practises (Just-in-Time (JIT), flexibility, and continuous improvement) on worker performance, workplace productivity, quality, and overall organisational performance. The outcomes of this research offer valuable insights and practical recommendations for textile companies aiming to enhance their employee and workplace performance through the adoption of lean manufacturing practices. Such implementation will help to reduce lead time, improve customer satisfaction, and increase productivity and efficiency.

Reducing emissions from production and distribution in three-echelon supply chains

Reducing carbon emissions is one of the key goals of contemporary supply chains and logistics. This paper aims to formulate a novel three-echelon (supplier-3PL-retailer) supply chain model comprising green technology investment, variable demand, variable lead time, a dynamic shipping strategy, and an option for vehicle selection. The demand function considers the product's freshness index and maximum lifetime, along with the availability of stocks. Besides, the delivery from the 3PL to the retailer is dynamically determined based on previous shipment information. A green vehicle is selected using a multi-criteria decision-making (MCDM) technique based on q-alternatives with n-characteristics for the transportation process and mathematically we link this selection process to traditional three echelon supply chain optimization problem. The results show that combining green investment with an appropriate dynamic shipping strategy by using a selected green vehicle reduces the supply chain's emissions and total integrated cost. Furthermore, reducing lead time without compromising other supply chain factors stimulates demand of customers and produces fewer emissions with a significant reduction in the total integrated cost. A real-case-based study shows the performance of the proposed model and method.. The study illustrates that 47.744% of the carbon emissions in Scenario 1 and 47.53% in Scenario 2 are reduced when an emission reduction strategy is implemented. In terms of total integrated costs our proposed model could save 4.85% cost in Scenario 1 while 4.96% for Scenario 2, which is significant.

Reduction of Lean Wastes by Using Value Stream Mapping: A Case Study of Textile Company in Pakistan

Purpose: Lean manufacturing, originating from the Toyota Production System (TPS), aims to reduce waste and optimize resources. Developed countries must adopt Lean practices for performance improvements while developing countries often use just-in-case approaches. Value Stream Mapping (VSM) is a crucial tool for diagnosing, implementing, and maintaining Lean Manufacturing, helping identify improvement opportunities and eliminating waste. The research at the company aims to eliminate Lean wastes and line unbalancing issues to improve lead time and the value-added ratio (VAR), enhancing production efficiency. The research aligns with Sustainable Development Goal 12 (Responsible Production & Consumption) by focusing on waste reduction.
 Methodology: The research uses time study, Edaw max, and Visio software to analyze tasks, create VSMs of current and future states, and control charts to examine data variations over time. Data collection involves cycle time, batch size, packet size, and the number of workers required for each activity.
 Findings: The research objectives include studying the existing scenario of production units via VSM, identifying, and eliminating Lean wastes, and comparing proposed and existing scenarios for improvement opportunities. The literature review highlights the importance of Lean manufacturing in eliminating unnecessary processes, reducing lead time, and fostering positive stakeholder relationships.
 Unique Contribution to Theory, Practice and Policy: This study suggests the better way to reduce the lean wastages and balance the line by using VSM technique. The future state VSM is created to conceptualize potential improvements and gather feedback, focusing on reducing non-value-adding tasks, work-in-process inventory, workforce, and overall process time.