Lead Time Reduction Research Articles

Interrelationships between process parameters, cross‐sectional geometry, fracture behavior, and mechanical properties in material extrusion additive manufacturing

AbstractAdditive manufacturing offers reduced lead time between design and manufacturing. Fused filament fabrication, the most common form of material extrusion additive manufacturing, enables the production of custom‐made parts with complex geometry. Despite the numerous advantages of additive manufacturing, reliability, reproducibility, and achievement of isotropic bulk properties in part remains challenging. We investigated the tensile behavior of a model polycarbonate system to explore what leads to different tensile properties, including sources of ductile versus brittle fracture. We utilized a one factor at a time (OFAT) design of experiments (DOE), printed single road‐width boxes, and performed tensile tests on specimens from these boxes. Additionally, we characterized the cross‐sections of parts printed under different conditions and their subsequent fracture behavior. The results demonstrate that isotropic bulk properties are achievable by printing at high speeds, and provide mechanisms to explain why.Highlights Printing at high speeds leads to improved mechanical properties. Printed samples undergo a mix of ductile and brittle failure. Jagged fracture path is associated with superior adhesion. High layer times lead to worse interfacial bonding.

Additive Manufacturing in Australian Small to Medium Enterprises: Vat Polymerisation Techniques, Case Study and Pathways to Industry 4.0 Competitiveness

The advent of additive manufacturing (AM) in Australian small and medium-sized enterprises offers the direct benefits of time-saving and labour cost-effectiveness for Australian manufacturing to be highly competitive in global markets. Australian local businesses can tailor their products to a diverse range of customers with a quicker lead time on the sophisticated design and development of products under good quality control in the whole advanced manufacturing process. This review outlines typical AM techniques used in Australian manufacturing, which consist of vat polymerisation (VP), environmentally friendly AM, and multi-material AM. In particular, a practical case study was also highlighted in the Australian jewellery industry to demonstrate how manufacturing style is integrated into their manufacturing processes for the purpose of reducing lead time and cost. Finally, major obstacles encountered in AM and future prospects were also addressed to be well positioned as a key player in the revolutionised Industry 4.0.

Transformative Procurement Trends: Integrating Industry 4.0 Technologies for Enhanced Procurement Processes

Background: the advent of Industry 4.0 (I4.0) innovations has revolutionized supply chain management through technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) integrated into procurement processes. Methods: this study addresses a critical knowledge gap by conducting a comprehensive review of 111 papers sourced from the Scopus database. These papers are classified into seven sub-themes encompassing I4.0 or procurement 4.0 (P4.0), big data, IoT, additive manufacturing, blockchain, e-procurement, and AI. Results: the investigation reveals that I4.0 technologies, particularly e-procurement and blockchain, have garnered substantial attention. Such technologies offer diverse value propositions, encompassing streamlined supplier evaluation, lead time reduction, cost optimization, and enhanced data security. Conclusion: the paper underscores pivotal trends and insights for the evolution of Procurement 4.0, illuminating a path toward more efficient supply chain management.

Low-Cycle Fatigue Behavior of Wire and Arc Additively Manufactured Ti-6Al-4V Material.

Additive manufacturing (AM) techniques, such as wire arc additive manufacturing (WAAM), offer unique advantages in producing large, complex structures with reduced lead time and material waste. However, their application in fatigue-critical applications requires a thorough understanding of the material properties and behavior. Due to the layered nature of the manufacturing process, WAAM structures have different microstructures and mechanical properties compared to their substrate counterparts. This study investigated the mechanical behavior and fatigue performance of Ti-6Al-4V fabricated using WAAM compared to the substrate material. Tensile and low-cycle fatigue (LCF) tests were conducted on both materials, and the microstructure was analyzed using optical microscopy and scanning electron microscopy (SEM). The results showed that the WAAM material has a coarser and more heterogeneous grain structure, an increased amount of defects, and lower ultimate tensile strength and smaller elongation at fracture. Furthermore, strain-controlled LCF tests revealed a lower fatigue strength of the WAAM material compared to the substrate, with crack initiation occurring at pores in the specimen rather than microstructural features. Experimental data were used to fit the Ramberg-Osgood model for cyclic deformation behavior and the Manson-Coffin-Basquin model for strain-life curves. The fitted models were subsequently used to compare the two material conditions with other AM processes. In general, the quasi-static properties of WAAM material were found to be lower than those of powder-based processes like selective laser melting or electron beam melting due to smaller cooling rates within the WAAM process. Finally, two simplified estimation models for the strain-life relationship were compared to the experimentally fitted Manson-Coffin-Basquin parameters. The results showed that the simple "universal material law" is applicable and can be used for a quick and simple estimation of the material behavior in cyclic loading conditions. Overall, this study highlights the importance of understanding the mechanical behavior and fatigue performance of WAAM structures compared to their substrate counterparts, as well as the need for further research to improve the understanding of the effects of WAAM process parameters on the mechanical properties and fatigue performance of the fabricated structures.

New Auto-Complete Software for CAM Programming Hits The Market

CloudNC's software CAM Assist has been launched and early adopters are reaping the rewards, with software opening up new opportunities, reducing lead times for components and boosting machine shop efficiency. CloudNC will take the software to this month's EMO trade show

Effects of process parameters and scan strategy on the microstructure and density of stainless steel 316 L produced via laser powder bed fusion

The ability to produce reliable and reproducible components from 316 L using additive manufacturing is crucial to serve the need for customization, on-demand manufacturing and reduced lead times for various industries. Laser powder bed fusion is becoming widely accepted as a versatile additive manufacturing technique capable of producing near defect-free components with tailored microstructures and mechanical properties. However, despite the recent progress in process parameter selection and optimization, even a small change in any of the laser parameters, equipment and feedstock powder characteristics can influence the microstructure and subsequently the mechanical properties of the fabricated parts. The purpose of this work is to tackle the process optimization challenge through, a full factorial design of experiments approach, to systematically assess the widely adopted energy density factor to evaluate the density of the final component. A statistical approach was also followed to evaluate potential plastic anisotropy in different samples produced with various energy densities and scan strategies. Density measurements indicated that beyond laser power and scan speed, the interaction effects of the aforementioned parameters with the layer thickness and the powder size distribution have a significant effect on the sample. Microstructural features such as melt pools, grains and crystallographic texture were characterized against a range of volumetric energy densities and scan strategies represented by different angles of rotation between successive layers. Smaller angles of rotation per layer were found to decrease texture anisotropy and suppress the formation of keyhole porosity in finer and more homogenous microstructures. The assessment of plastic anisotropy in the produced samples was evaluated using microhardness measurements on all three orthogonal planes of the samples. The hierarchical microstructure of laser powder bed fusion materials induces several strengthening mechanisms, that can simultaneously be activated depending on the loading scenario, location and plane.

The Role of Supply Chain Integration and Agile Practices In Improving Lead Time

Lead time is one of the main factors which always significantly affects supply chain competitiveness. The recent COVID-19 pandemic has harmed the lead time, and an exceptional increase in the lead time has been experienced because of it. However, there are a few variables which can have a positive effect on the lead time. Aim: This research study was aimed at how the variables like Agile Practices and Supply Chain Integration may influence lead time. Methods: Research data was collected from the respondents, who were supply chain executives and managers, through a closed-ended questionnaire, and the Statistical Package for Social Sciences (SPSS) was employed to drive the results. Results: The findings of this study indicates that Supply Chain Integration and Agile Practices contribute to the reduction of lead time. Conclusion: Findings also suggest that the lead time can be significantly reduced with the employment of Supply Chain Integration and Agile Practices.

The Role of Computer-Aided Design (CAD) in Welding and Fabrication Projects

The integration of Computer-Aided Design (CAD) into welding and fabrication projects has brought significant advancements to modern manufacturing. This study explores the multifaceted role of CAD in these processes, investigating its influence on design accuracy, manufacturing efficiency, and cost-effectiveness. Through surveys, case studies, and expert interviews, the study uncovers a substantial adoption rate of CAD among engineers and highlights its positive impacts. Design iterations are reduced by 20%, manufacturing efficiency gains a 15% lead time reduction, and cost-effectiveness improves by 18% due to minimized material wastage. However, challenges like the learning curve and interoperability issues persist. Recognizing these benefits and challenges, this research contributes to the understanding of CAD's transformative influence on welding and fabrication, enabling industries to optimize processes and enhance product quality.

DevOps Practices and their Role in Streamlining Information System Development

This study delves into the realm of modern software development by investigating the role of DevOps practices in streamlining information system development. Employing a qualitative research approach, a blend of in-depth interviews and comprehensive surveys were conducted to capture insights from professionals in software development and operations roles. The findings reveal a prevalent adoption of DevOps practices, with 70% of interviewees and 65% of survey respondents indicating integration. Notably, Continuous Integration (CI) emerged as a cornerstone practice, fostering rapid code integration, while Automated Testing fortified software quality. Enhanced collaboration and reduced lead times signify the potency of DevOps's impact on development cycles. However, challenges in cultural transformation and effective automated testing suites underscore the journey's complexities. Ultimately, the study illuminates DevOps as a catalyst for collaborative agility and a transformative force shaping the software engineering landscape.

Engineering-to-order manufacturing: A criticality analysis of key challenges and solutions based on literature review

Engineer-to-Order (ETO) manufacturing companies involve customised production products based on specific customer requirements, and face a significant challenge. Some of those challenges are related with this type of company’s activities in production scheduling, planning and control, efficiency improvement and lead time reduction. The present study was conducted with a systematic literature review and a survey from ETO firms to identify the most frequent and critical problems. Among the most critical issues identified is the difficulty in optimising production performance (P3), with a GCI value of 16, implying that both time and cost share the same critical level. An analysis using a proposed Criticality Matrix was then performed enabling companies to prioritise decision-making and resource allocation. The results highlight the importance of adopting mass customisation strategies, innovative approaches and workflow optimisation. Continuous monitoring and analysis of criticality levels can also help ETO companies identify emerging issues and improve informed decisions. Effective communication and collaboration among stakeholders were also identified as vital. Future research could be done expanding further the study sample and developing decision-support tools for ETO manufacturing companies. This study contributes to the field by providing a new criticality matrix for ETO companies to understand better and address their production challenges, aiding in decision-making and resource allocation.

Experimental Investigation of Spatter Particle Behavior and Improvement in Build Quality in PBF-LB

Laser powder bed fusion with metallic materials as a heat source (PBF-LB/M) is an additive manufacturing (AM) technique that has been applied in various industrial fields to reduce component weight, improve functionality, lower manufacturing costs, and reduce lead times. However, detailed characterization of the PBF-LB/M phenomenon is challenging because of the mutual influence of laser parameters and chamber environment. In PBF-LB/M, the powder is repeatedly melted and solidified by laser irradiation. However, the hot spatter generated in the process causes defects and insufficient melting. In this study, we use a high-speed camera to observe hot spatter ejected from the laser-irradiated area of a commercial PBF-LB/M system and investigate the effects of inert gas flow and laser scanning strategy on hot spatter behavior. We found that the ejection velocity of hot spatter immediately after ejection from the melt pool decreases as the particle size increases and is not affected by gas flow velocity. Furthermore, we observed that hot spatter is always ejected behind the laser scanning direction, but the ejection direction of the hot spatter changes over time. Particularly, when the laser scanning direction follows the gas flow direction, the spatter ejected in the backward direction of the scanning direction may follow a large curve over time to the front of the scanning direction and deposit on the build part. Based on the results of these investigations, we drew conclusions on the effect of the laser scanning direction with respect to the gas flow direction on the build quality and found that scanning the laser in the opposite direction to the gas flow is more effective in improving the surface quality.

Assembly operation productivity improvement for garment production industry through the integration of lean and work-study, a case study on Bahir Dar textile share company in garment, Bahir Dar, Ethiopia

Productivity improvement is a significant issue for the textile and garment industry to survive global competition. Therefore, the nation's efforts towards this improvement are one of the key weapons to attain cost, time, and quality advantages for rivalry. Ethiopian garment industries are not competitive due to low productivity, which is caused by multidimensional productivity factors related to humans, methods, control, processes, and products. Hence, a single tool or simple model cannot boost significant change for productivity improvement and cannot solve both internal and external productivity factors of the garment industry at this time. However, combined techniques or tools of lean and work-study are preferable. Lean manufacturing is a procedure to identify and eliminate non-value-adding activities in a consistent, continuous improvement. Lean techniques provide a good overview of the processes, whereas work-study methods focus on the critical areas of the operation. This research deals with productivity improvement in the assembly operation of the garment industry with a case study using integrated techniques and tools, such as line balancing, work standardization, time and method study, total working method, and process improvement related to kaizen and 5S. These tools help to eliminate non-value-adding activities were reduce lead time, and defects. The study illustrates, using a case study, the most critical factors that hinder the productivity of Ethiopian garment industries and how to solve these factors through integrated techniques or tools. The research is practical and realistic, and the necessary data was collected using primary and secondary data from the Minister of the Ethiopian garment industry and the case garment. The observed results indicated that non-value-adding activities were minimized from 43% to 5%, bottlenecks from 3 to 0, and the transportation distance of the workers was reduced by 650 m per shift. The daily production output of the case garment and main exports of Flat sheet and Quilt cover products increased from 43.3% to 57.7%–75.8% and 100% pcs per shift, respectively. The standard time for each operator can be set using time study, which can save 315 min for the case garment operation, achieving its production targets of 800 pcs per shift. Therefore, using a single tool or model has not significantly improved this garment industry, but it should be used as a combined tool of lean and work-study for attractive productivity improvement.

Post processing of low cost Aligners fabricated by additive manufacturing process to enhance the surface quality and functionality

Additive Manufacturing (AM) processes have ample advantages compared to traditional manufacturing processes, including mass customization, material efficiency, bioprinting, and fabrication of complex geometries with reduced lead time. Despite such benefits, it suffers most from staircase effects that deteriorate the fabricated part's surface quality. Nowadays, additively manufactured aligners are suitable for treating malocclusion and temporomandibular defects of teeth. Fused Deposition Modelling (FDM) is one of the best substitutes for clear aligners production to reduce per-unit cost. Glycol-modified Polyethylene Terephthalate (PETG) is opted as the material to fabricate the clear aligners due to its biocompatibility and non-toxicity. However, the poor surface quality of the additively manufactured is a major challenge in developing clear aligners with the FDM. A novel experimental setup is designed and developed to enable Chemical Vapor Smoothing (CVS) to enhance the surface quality of the clear aligners. Furthermore, based on the Surface roughness, the comparison is made between the surface quality polished with various chemicals (namely methylethylketone (also known as 2-butanone), toluene and, cyclohexanone). Moreover, Response Surface Methodology (RSM) is used to analyze the impact of different process parameters (i.e., the chemical volume, exposure time, and workpiece orientation) on the surface quality of the clear aligners. Moreover, RSM shows that the impact of the clear aligners orientation on %ΔRa during the CVS is higher than other process parameters. Results demonstrate that cyclohexanone produces more uniform surface quality with a 92.73% reduction in surface roughness compared to methylethylketone and toluene on PETG, i.e., 89.66% and 88.63%, respectively. The developed surface finishing method is capable of producing uniform, smooth surfaces over the FDM-fabricated PETG clear aligners.

تطبيق نظام التصنيع بالاستجابة السريعة (QRM) في الشركات الصناعية السودانية وأثره على خفض التكلفة وتحقيق الميزة التنافسية للفترة من 2017-2021 (دراسة تحليلية)

The study aimed to shed light which the quick response manufacturing system (QRM) can be applied in Sudanese industrial companies and its impact on reducing costs and achieving competitive advantage by reducing lead times and deleting activities that do not add value and the consequent reduction in cost and speed in completing production processes and work orders In general which leads to gain customers confidence in the price and quality of products and thus increasing the competitive advantage. The research objective identifies the methods and elements of the quick response manufacturing system which are used to influence cost reduction and achieve a competitive advantage in Sudanese industrial companies. The researcher has used the deductive approach when choosing a problem, the study and the development of scientific hypotheses. In addition to, the statistical analysis that has relied on the field study. The study population and sample consist of a group of accountants, production managers, engineers and technologists. The most important results By testing the hypotheses of the study, it was found that the value of the (t) test is )23.847( with a degree of freedom of 102 and a significant level (0.000), which indicates a statistically significant relationship between the Sudanese companies' application of the quick response manufacturing system and cost reduction and an increase in competitive advantage by 95%. This means that the Sudanese industrial companies that applied this system during the study period achieved a cost reduction and that the speed of their response by increasing their market share of products leads to attracting new customers, thus achieving a competitive advantage in the local and global markets.. The study has recommended that Sudanese industrial companies adopt the quick response manufacturing system as a comprehensive applied strategy that includes an intellectual tendency that seeks to severely and continuously reduce production deadlines and develop scientific competence and skills by urging with industrial company managers’ and production managers to participate in conferences and seminars held by professional people related to the quick response manufacturing system.

A sustainable supply chain coordination model with an investment in green technology and electric equipment

This paper proposes a new mathematical model to examine a solution to a sustainable supply chain problem by investing in green production technology and electrical equipment for transportation and warehousing. This study integrated an inventory model involving a single vendor, a single distributor, and multiple retailers. The carbon emissions involving emissions from a vendor and retailers are incorporated in this paper. An algorithm solution is proposed to minimise the total cost to determine the optimal decision variables, i.e. the lot size, number of deliveries, safety factor, lead-time, and emissions. A numerical example is illustrated to validate the proposed model and provide insight into the relevant industry. The life cycle cost assessment of the electrical equipment is also discussed for managers to inform their decision-making. From the comparison results, the integrated scheme comprising electric-powered with green investment is lower than without green investment, fossil-fuel with green investment, and fossil fuel equipment only with a total cost saving of 0.68%, 3.28%, and 3.59%, respectively; lower-emissions of 39.69%, 42.22%, 27.46%, respectively; and lead-time reduction of 1.80%, 25.23%, 23.78%, respectively.

Production and Internal Logistics Flow Improvements through the Application of Total Flow Management

Background: Nowadays, as a result of globalization, markets are more competitive, and customers are more demanding. To respond to these challenges, organizations must develop mechanisms for continuous improvement in order to eliminate waste and increase the efficiency and effectiveness of processes. Thus, the present study carried out at an industrial unit responsible for the customization of cork stoppers for wines had as its main objectives to identify and eliminate or at least reduce waste; improve production and internal logistics flows; balance workloads; improve productivity; reduce lead time; motivate employees and promote the spirit of continuous improvement. Methods: The action-research methodology was used, whereby several cycles of data recovery and analysis, identification and implementation of opportunities for improvement, assessment and standardization were carried out. Therefore, the Total Flow Management (TFM) model was implemented, and several methods and tools were used, such as Value Stream Mapping (VSM), work measurement and 5S’s. Results: Several wastes and overloads were identified, and some actions were implemented, such as workload balancing, layout changes, implementation of visual management and supermarkets. That said, it was possible to reduce lead time by 4 days, improve productivity from 26.63 ML (a thousand cork stoppers)/h to 35.75 ML/h, and promote flexibility. In addition, employees were motivated, and a culture of continuous improvement was fostered. Conclusions: This project demonstrated that it is possible to implement improvement actions, with good results, without high investments, as well as motivating employees and taking advantage of their best capabilities. Additionally, it was demonstrated that the use of TFM can be very useful in continuous improvement, with evident improvements in production and internal logistics flows. So, this project demonstrated the practical implementation of TFM regarding basic reliability, production and internal logistics flow, and the simultaneous use of several methods and tools to implement continuous improvement. Thus, significant improvements were possible on the factory floor, as well as improving employee motivation their personal development and encouraging the focus on continuous improvement. Therefore, it responds to the gap identified in the literature.

Comparative analysis of lean and agile supply chain strategies for effective vaccine distribution in pandemics: A case study of COVID-19 in a densely populated developing region

Mass vaccination programs should employ effective strategies to design a resilient vaccine supply chain for immunizing populations quickly and efficiently. The need for more flexible and responsive vaccine supply chain design is highlighted during the pandemic, where authorities are required to effectively execute vaccine distribution. Our study proposes a scientifically driven approach to identify suitable supply chain strategies for vaccine distribution, enhancing the effectiveness of mass vaccination. We propose a two-stage approach for identifying the best supply chain strategy that supports faster vaccine rollouts, reducing infections and deaths during the pandemic. We optimize the vaccine distribution network under both supply chain strategies using Mixed Integer Programming (MIP) for four disruption scenarios in the first stage. Second, we have used systems dynamics simulation and the Susceptible-Exposed-Infectious-Recovered (SEIR) model for pandemics to identify the impact of vaccination. In all disruption scenarios, vaccine distribution using the Lean strategy is less costly, and the Agile strategy reduces lead time and supports faster vaccine rollout. We show achieving a cost-saving or lead-time saving using either supply chain strategy becomes increasingly difficult when the severity of disruptions at storage increases. Our study suggests a novel methodology that determines the most suitable strategy for vaccine distribution which minimizes infections and deaths under several disruption scenarios. The decision-makers can identify appropriate supply chain strategies for vaccine delivery to densely populated developing regions, using the proposed framework which compares supply chain strategies’ impact on vaccine distribution network design.

Channel Changes Choice: An Empirical Study About Omnichannel Demand Sensitivity to Fulfillment Lead Time

We examine a large transaction-level data set of an Italian omnichannel furniture retailer to study channel-specific effects of fulfillment lead time on demand. This omnichannel retailer sells the same products and has the same product fulfillment across three channels: showroom, online, and catalog. The showroom channel carries no inventory but allows customers to touch and feel the products. The online channel provides a website for consumers to browse and order the products. The catalog channel sends a product catalog to all the households in Italy, so they can place an order over the phone. We find that the showroom channel makes consumers less sensitive to fulfillment lead time than both online and catalog channels. In particular, a 10% increase in lead time (1.83 days from the sample mean of 18.26 days) causes a 0.29% reduction in the daily sales volume (approximately 29 units from the sample mean of 10,140 units per day) at the showroom, which is less than the reduction of 1.85% and 0.92% in the online and the catalog channels, respectively. This finding contradicts the common practical and theoretical assumption about homogeneous lead time sensitivity across channels. In addition, we find that niche products and experience goods accentuate the difference of lead time sensitivity between showroom and nonphysical channels. Through an online experiment, we show that higher product information precision, such as that provided in a showroom, can alleviate customers’ anxiety around product uncertainty, thus reducing lead time sensitivity and increasing purchase intent. We further build two analytical models to show the implications of our empirical results for showroom network design and inventory rationing decisions. Our study highlights the previously ignored fulfillment time sensitivity aspect of the physical store’s value. This paper was accepted by Vishal Gaur, operations management. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4839 .

Review of Using Technologies of Artificial Intelligence in Companies

Artificial intelligence (AI) has become increasingly prevalent in business as companies adopt machine algorithms that can learn and improve over time. These AI-powered solutions are used in various business areas, including operations, analytics, product personalisation, marketing, sales, customer service, and human resource (HR). AI can help companies automate mundane tasks, make smarter decisions based on data and insights, and provide capabilities for smoother customer experiences, better customer service, and increased efficiency. AI has also allowed companies to enhance the quality of their digital services, optimise supply chain processes, and gain access to real-time insights and analytics. Companies can use AI to reduce lead times, generate new customer insights, improve customer service, and create meaningful customer experiences. This paper aims to address the gap in knowledge on incorporating AI into business strategy by conducting a critical literature review, synthesising current approaches and frameworks, highlighting potential benefits, challenges, and opportunities, and discussing future research directions.

Analyzing blockchain-based supply chain resilience strategies: resource-based perspective

PurposeThis research tries to find the blockchain-based resilience strategies that can help the supply chains of micro, small, and medium-sized enterprises (MSMEs) to recover from the disruptions and work effectively in a resource-based view perspective.Design/methodology/approachEight broad strategies and 32 sub-strategies are identified from the literature review. Delphi study was carried out, and detailed discussion with 16 experts helped in finalizing these strategies. Further, the best-worst method (BWM) prioritized these strategies.FindingsThe findings suggests that “building social capital,” improving “coordination capabilities,” “sensitivity towards market,” “flexibility in process and production,” “reduction in process and lead time,”and “having a resource efficiency and redundancy” are the top strategies on which the top management should focus to overcome the situations of disruptions and enhance performance of MSMEs.Practical implicationsThe blockchain-based strategies will enable the companies in tracing the products from the company to customers. Further, the customers will be able to identify their manufacturers, the raw materials used in manufacturing, and the life and quality of raw used materials. Altogether the textile industry will become more sensitive toward environmental practices.Originality/valueThe previous research has not identified and evaluated the blockchain-based resilience strategies, and therefore this study tries to fill this gap. This study used a smaller sample from the experts, so the results may vary if the larger data set is used and hypothesis testing can be done.