Production Lead-time Research Articles

An Approach to Reduce Production Lead Time in the Valve Manufacturing Industry

Lean manufacturing aids improved productivity and product quality by identifying and eliminating waste. The present work aims to utilize Value Stream Mapping (VSM), a lean manufacturing technique to minimize the cycle time in the production of valves. A current state map is developed with available information gathered from the production unit, to identify the time-consuming factors like waiting time, improper inspection, and the lack of material and resources for manufacturing. Problem-solving techniques like 5s, JIT, KANBAN, and KAIZEN are used to reduce time-consuming activities. Value-Added and Non-value-added activities are identified through Current State Map. Activities such as placing a purchase order, drawing, assembling, testing, packaging, and shipping are Value-added activities. Non-Value-added activities are identified as rework, inspection, movement, waiting for the next process, and over-processing. The job waiting time between the next process is reduced by 70% using the future state map and the productivity is enhanced.

2021 UK floods: improvements and recommendations from the flood forecasting centre

Abstract In recognition of the increased risk to national resilience from flooding, we provide an overview of recent and future improvements to flood risk forecasting and communication at the Flood Forecasting Centre (FFC). We draw on the analysis of fluvial and surface water flooding across England and Wales in 2021 to highlight these areas of improvement. Already implemented improvements in both the underpinning science and our long lead-time product are described in the context of high-magnitude, high-impact floods. In addition, we consider more substantial developments from improved modelling of convection to translating this to surface water flood risk and to the essential communication and service provision. Finally, recognising that many of the challenges are shared internationally, we distil our key recommendations for future improvement. These improvements rely on collaboration for them to be successful.

Analysis of a dual-channel green supply chain game-theoretical model under carbon policy

In today's worldwide markets, supply chain members have to control carbon emissions for a clean environment. This study addresses a dual-channel green supply chain model by contemplating dual selling channels, carbon diminution rate and online delivery lead-time as marketing efforts to fascinate customers to buy more products. Moreover, the carbon tax protocol, green technology, carbon cap-and-trade protocol are applied to the supply chain to save the environment by reducing carbon emissions. The customers' demands for both the direct and traditional retail channels are dependent on direct selling price, retail price, carbon reduction rate, and delivery lead-time of online products. The objective of this work is to maximise the supply chain profit by minimising the amount of carbon emissions. To determine optimal outcomes, a centralised system, manufacturer-leadership Stackelberg game and retailer-leadership Stackelberg game are employed. A comparison among the centralised system and the two Stackelberg games is also carried out. The results presented that to enhance the profits of the manufacturer as well as retailer and to decline carbon emissions, manufacturer-leadership Stackelberg game is the adequate game policy. Some managerial inspirations of this proposed work are listed. The paper ends with conclusions and possible future research directions.

Energy consumption optimization for sustainable flexible robotic cells: Proposing exact and metaheuristic methods

Many manufacturing companies are always looking for a way to reduce energy consumption by utilizing energy-efficient production methods. These methods can be different depending on the type of products and production technology. For instance, one of the ways to increase energy efficiency and keep the precision of production is to use robots for the transportation of the parts among the machines and loading/unloading the machines. This technology is affordable compared to the technologies used in manufacturing companies. Manufacturing companies that rely on robotics technology must have a strategy to reduce energy costs and at the same time increase production by adjusting the intensity of processing or controlling the production rate. This study presents an exact solution method for flexible robotic cells to control the production rate and minimize energy consumption, which aims to both reduce electricity prices and minimize greenhouse gas (GHG) emissions under a lead time of production. Then, considering the NP-hardens nature of the problem, a heuristic solution method based on the genetic algorithm (GA) is proposed. Using the proposed approach, manufacturing companies will be able to make more accurate decisions about processing intensity and process scheduling while ensuring sustainability.

Production lead-time hedging and order allocation in an MTO supply chain

In an make-to-order (MTO) supply chain, as consumers are increasingly sensitive to the delivery time and delivery reliability, quoting a short delivery time while delivering on-time is the major challenge for the retailer. To avoid tardy delivery, the retailer usually requires the manufacturer provide reliable delivery service by hedging against its production uncertainty, which is termed as production lead-time hedging (PLTH). To examine the effect of PLTH strategy on delivery time decision and profits for both retailer and manufacturer, we develop two game models. To our best knowledge, this paper is among the first that study delivery time quotation while considering delivery reliability and production uncertainty control. Furthermore, as multi-sourcing becomes more and more popular, we extend the basic single sourcing model to the multi-sourcing model. The main methodological contribution is the development of a traceable game theoretical model that links operational hedging decisions and order allocation implication, whilst considering delivery unreliability. Our findings show that adopting the PLTH strategy, which enables the retailer to quote a short delivery time in most cases, is the dominant strategy for the retailer. Especially, the multi-sourcing outperforms the single sourcing. The single sourcing Nash game also benefits the manufacturer. However, in the single sourcing Stackelberg game, the manufacturer will join the PLTH strategy only when the consumer's delivery time sensitivity is not sufficiently large. Interesting, when the consumer's delivery time sensitivity becomes sufficiently large or the consumer's on-time delivery sensitivity becomes sufficiently small, the retailer will scarify the on-time delivery reliability.

Analysis of Lean Manufacturing Implementation on E-Supply Chain Management Performance in Manufacturing Companies

This study aims to determine the effect of the implementation of the lean manufacturing system on the performance of E-supply chain management. The sample for this study is a company that uses a lean manufacturing system in Cikarang, Bekasi. This research method involves using direct observation in companies regarding the use of lean manufacturing systems from the processes of receiving customer orders, calculating raw material requirements, ordering raw material requirements, production processes, and delivery processes, so that concrete data can be obtained. With this research, it will be determined whether the use of a lean manufacturing system will affect production lead time, reduce the amount of inventory, reduce inventory area, and improve delivery performance. So that from the implementation of lean manufacturing, is there any influence on the performance of E-Supply Chain Management. With E-Supply Chain Management, control and monitoring of Supply Chain Management performance can be done in real time, wherever we are as long as there is an internet network, we can control.

Investments in digital technology advances in textiles

The investments in digital technologies are expected to soon have a major impact on the textile and fashion companies’ sustainability and competitiveness. Motivated by these trends empirical research on investments of the fashion and textile companies in ICT technologies-based advancement in the Serbian case was provided in 2022. Representatives of 423 textile and fashion companies were asked about their investments in various digital technologies in the previous three years and their digital transformation status. The research findings show that investments in cloud computing, IT, energy management, automation, robotics, and machine learning technologies have a significant impact on the digital transformation of companies. Most of them reached a medium level of transformation, fewer than a high level, with many textile and fashion companies just defining digital transformation. The contribution of the research findings to the investments in the companies’ digital transformation can be seen in the significance of the textile’s digital technology implementation, which enables manufacturers and retailers to respond directly to market demand by reducing product lead time and cost, increasing supply chain efficiency and profitability, and promising in terms of ensuring competitive advantage in the risk and challenging business environment.

Adopting Value Stream Mapping as a Lean Tool to Improve Production Performance

The main challenge facing industrial companies is how to stay competitive in a fast changing world. They should adopt an effective supply chain that enables them to deliver products in a short period of time. This forced organization to change their pattern of processing and become lean. Lean manufacturing system is the best philosophy to achieve the objectives of the industrial organizations and to reduce the waste activities. The unnecessary movement, defective, waiting, inadequate processing, unnecessary inventory, excessive transport, overproduction, and the underutilization of people and facilities are the most types of waste found in the industries. Many industries have experienced the benefits of applying the lean concept in their area to improve the production processes, resources utilization, reduce production lead time, and eliminate wastes in the activities which is the goal of lean concept in the manufacturing industry. In this research, the lean concepts are presented in the leather shoes manufacturing industry in the city of Baghdad, it aimed to decrease the lead time of production, minimize the non-value time, and improve the production line. By using the most essential lean tool, value stream mapping, where the current and future map capture the flow of material and information of the production line before and after the implementation of the proposed improvement. The hybrid push/pull strategies and Kanban production were implemented to improve the production line. After adopting the suggested improvement, the production lead time reduced from 130.6 to 14.8 hours and the non-value added reduced from 118 to 10.8 minutes.

How to Manage Relations Facing Accumulated Supply Chain Disturbances: Pandemic, War and Ripple Effects

How to develop a suitable management style to manage external Supply Chain network relations in the light of unprecedented external disturbances like the Covid pandemic, Ukraine war and inevitable ripple effects caused by explosions or strikes? Impacts in terms of increased lead times, uncertainty about the time required by suppliers and buyers for decision making. But, it also should be suitable in dealing with quite different types of managerial attitudes encountered. The mixed-methods analysis of a 3 tier supply network around a small focal printing company shows that (1) total lead time for raw materials, production and delivery went up from 9 days to 60 days or more. It not only meant increased uncertainty for the focal company but also for its B2B buyers; (2) the decision time of buyers responding to requests to accommodate changes enforced by scarcity or increased lead time of raw materials varied between 3 and 41 days, depending of the size of the buying firm where four size categories were used. Small SMEs were fast deciders but being mostly negative in attitude; multinationals were slow but more flexible and cooperative. (3): zooming in on the managerial or human attitudes encountered in 100 contacts with buyers revealed 9 different human attitudes that could be clustered into a scale with two extremes: Total denial (selfish, exploitative, demanding, brutal, ignorant, helpless) versus Total flexibility (cooperative, tolerant, inspiring). (4) To deal with these different attitudes employee training is recommended, using the DiSC portfolio model invented by William Moulton Marston, standing for Dominance, Influence, Steadiness and Compliance (sometimes referred to as Conscientiousness).

Additively manufactured IN718 in thin wall and narrow flow channel geometries: Effects of post-processing and wall thickness on tensile and fatigue behaviors

Using additively manufactured (AM) tubular IN718 specimens, this study was conducted to understand the effects of wall thickness, surface machining, and hot isostatic pressing (HIP) on tensile and fatigue behaviors. The tubular specimens with thin wall (TW) features and narrow flow channels (NFC) had machined external surfaces and a combination of different internal surface (machined vs. unmachined) and heat treatment (with HIP vs. without HIP) conditions. On one hand, in terms of tensile properties, HIP was found to decrease strength while slightly improving ductility under quasi-static loading. Both surface machining and larger wall thickness were found to improve ductility without influencing the strength. On the other hand, HIP, surface machining, and wall thickness had no measurable influence on fatigue performance in the low and mid cycle fatigue regimes. Some positive effects of wall thickness on fatigue life were noticed in the high cycle fatigue regime for TW specimens undergone HIP and internal surface machining. The results suggested that the post-processing steps of AM IN718 TW and NFC parts could potentially be eliminated to reduce production cost and lead time if the targeted applications were fatigue critical in low and mid cycle fatigue regimes.

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

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

Quality improvement in cutting process of window tint using DMAIC approach

In this study the DMAIC (Define, Measure, Analyse, Improve and Control) technique is applied at a company producing window tint film forming and cutting in Malaysia. It is a company initiative for continuous improvement. The study's goal is to reduce the number of faults during the film cutting process, which has a significant impact on the company's overall profit margin and also affects production lead time. The research looks at the cutting process production line with the greatest defect rate. Quality Control (QC) methods such as brainstorming, process mapping, fish bone diagram, Pareto chart, and FMEA were used in the study. At the analysis stage, the key contributors to the defect problems can be identified, and action or solutions can be implemented. The study demonstrates that the DMAIC process is a successful approach for resolving what appears to be a huge problem with simple approaches. DMAIC has the ability to provide high returns to the company if implemented appropriately and effectively.

A Data-Characteristic-Driven Decomposition Ensemble Forecasting Research on the Demand of Space Science Payload Components

In order to solve the problem of long product lead time, accurate demand forecasting for space science payload components is of great significance to the development of China’s space science industry. In view of the unsteady, nonlinear, and small sample characteristics of space science payload component demand, this paper proposes the EEMD-CC&CV-MPSO-SVR model to predict the future demand of space science payload components. First, this paper effectively adopts EEMD to decompose the normalized demand sequence and analyze the stationarity of each subsequence. The sequence complexity is distinguished by sample entropy, and the optimum kernel function CC-MPSO-SVR and CV-MPSO-SVR prediction models are established for high-complexity and low-complexity sequences, respectively. Finally, the prediction results of each subsequence are ensemble to form a total prediction. Experimental results shows that the model proposed in this paper performs better than single benchmark models and other hybrid models in terms of prediction performance and robustness. It can effectively predict the quantity and trend of the demand for China’s space science payload components, which provide decision-making basis for the government to formulate policies, demand-side procurement, and supply-side inventory control.

Bi‐objective optimization of the tactical allocation of job types to machines: mathematical modeling, theoretical analysis, and numerical tests

AbstractWe introduce a tactical resource allocation model for a large aerospace engine system manufacturer aimed at long‐term production planning. Our model identifies the routings a product takes through the factory, and which machines should be qualified for a balanced resource loading, to reduce product lead times. We prove some important mathematical properties of the model that are used to develop a heuristic providing a good initial feasible solution. We propose a tailored approach for our class of problems combining two well‐known criterion space search algorithms, the bi‐directional ε‐constraint method and the augmented weighted Tchebycheff method. A computational investigation comparing solution times for several solution methods is presented for 60 numerical instances.

Enhance quality improvement through lean six sigma in division Side Board Clavinova Piano’s

A lean production system is one of the main factors that every company must have to improve quality, especially reducing waste that occurs in the production line. The musical instrument industry such as Piano manufacturing includes industries that reduce waste by improving the manufacturing system. The company’s strategy to eliminate this waste is to create an effective and efficient work system. The piano production process still has several problems, such as the presence of waste. This is an obstacle in improving the quality of production by reducing the waste that occurs. For this reason, this research focuses on improving the quality of production by reducing waste that occurs, finding the cause of the problem and taking corrective action. The method used in this research is the integration of Lean and Six Sigma and the DMAIC framework. The process is waste flow and production problems are identified in Define phase and residual measurement is measured in Measurement phase. Fishbone diagrams and the application of FMEA are used to analyze the factors that cause problems that occur and prioritize improvements to solve these problems. The implementation of Value Stream Mapping (VSM) is applied to the Enhance of quality improvement phase to reduce waste. The results showed that product quality increased from an average sigma level of 3.53 to 3.79 where overproduction decreased by 41% and Side Board production leadtime decreased by 373 second.

Interrelated process-geometry-microstructure relationships for wire-feed laser additive manufacturing

Wire-feed laser additive manufacturing is an emerging fabrication technique capable of highly automated large-scale volume production that can reduce both material waste and overall cost while improving product lead times. Quality assurance is necessary for implementation into critical structural applications. However, the large number of process variables along with the cost associated with traditional trial and error methods makes this difficult. This study investigates interrelated process-geometry-microstructure relations based on learning from experiments that will enable improved quality control along with consistent overall surface, geometric and microstructural features of the part. Specifically, an experimental dataset across multiple process variables and output characteristics in terms of overall bead quality, geometric shape (i.g. bead height, width, fusion zone depth, etc.), and microstructures are collected. The predicted process-geometry-microstructure relations are then captured by virtue of data-driven machine learning models. The properties of printed beads are visualized based on an extensive range of processing space within a 3-dimensional contour map. The insights and impacts of process variables on bead morphology, geometric and microstructural features are comprehensively investigated for quality improvement during manufacturing processes.

A two-tier supply chain model under two distributions with MTTF, rework, variable production rate and lead time

This article considers the two-level supply chain model incorporating an imperfect production process under a variable lead time. The cost of producing a unit item is calculated as a function of the production rate. In addition, two alternative production functions (linear and quadratic functions) are used to relate process quality and production rate. Lead time demand follows two different distributions, based on which two mathematical formulations are described in this paper. In the first model, the lead time demand follows a normal distribution. In the second model, the lead time demand doesn't follow any particular distribution, but the mean and the standard deviation are known. The lead time length is minimized by incorporating the lead time crashing cost. This research aims to analyze the optimized total cost of the supply chain under two different distributions.

Production lead time improvement through lean manufacturing

Production lead time improvement through lean manufacturing

Applying Integrated QFD-MCDM Approach to Strengthen Supply Chain Agility for Mitigating Sustainable Risks

As the global economy develops and the complexity of supply chains increases, the effective mitigation of sustainable supply chain risks in electronics manufacturing has become important. While quality function deployment (QFD) has been successfully applied to many fields of multicriteria decision-making (MCDM), there is a lack of research on constructing a house-of-quality model that can be combined with MCDM for connecting supply chain agility with sustainable supply chain risks, especially in the field of electronics manufacturing. The objective of this study was to develop an integrated framework of QFD and MCDM and to devise an effective method to mitigate sustainable supply chain risks by improving supply chain agility. Such a method can help the multinational electronics manufacturing industry to develop stable and sustainable supply chains. In a multinational electronic manufacturing enterprise as an example, the results showed that the case enterprise work should focus on improving agility ‘production and sales capability’, ‘quick decision-making/strategic flexibility’, ‘electronic shiapment of finished products to control shipment operations’, ‘supplier on-time delivery rates’ and ‘cost minimization’. Improving agility would help enhance the ‘credibility and competence of operators and leaders’ and ‘product safety and quality’ and reduce ‘goods disruption or delay due to inadequate supply mobility and poor financial performance’, ‘information system instability’, the ‘long product lead time’ and other key sustainable supply chain risks. The proposed framework can not only be effectively used by other electronics manufacturers to develop agile strategies to mitigate sustainable supply chain risks, but also provides a reference for risk management for manufacturers in other fields.

Production lead time improvement through lean manufacturing

The study presents the application of a lean manufacturing system in Hibiret Manufacturing and Machine Building Industry (HMMBI). The aim of the research is to improve the production lead time by minimising non-value adding activities. Both qualitative and quantitative data are used. The movement of production activities is drawn by the spaghetti model. Value-added and non-value added activities are identified using value stream mapping (VSM). Minitab quality companion and SigmaXL tools are employed to draw VSM and generate the value of performance indicators respectively. After identifying the bottleneck areas, suggested measurements are taken. As a result, work in process time is reduced by 50.37 hours, waiting time reduced by 50.37 hour, process cycle efficiency is enhanced by 8.6% and the travel distance is reduced by 951 metres. Finally, production lead time is improved by 50.361 hours. Thus, it is concluded that the research has found a significant benefit for HMMBI and similar manufacturing industries.