Production Cycle Time Research Articles

Reducing product cycle time and costing using screwed Yoke design for industrial globe valves

The objective of this project is to using screwed yoke design instead of existing welding design to the reducing product cycle and cost of an Industrial Globe Valves starting from marketing, getting the order from customer, manufacturing and supplying to customer, find the bottlenecks and suggest solutions to optimize the product cycle time and reduce cost of this valve with customer satisfaction. We used screwed yoke instead of welded yoke of the valves to perform the main objective of this study.

Study on structural optimization of braid‐and‐lay integrated carbon fiber reinforced polymer for metro bogie

AbstractCarbon fiber reinforced polymer is an effective solution for replacing metal materials and achieving lightweight, and both three‐dimensional (3‐D) braided composites and prepreg laminated composites have their strengths and weaknesses. Using only one forming process can be challenging to meet the performance requirements of structural components under complex operating conditions. To effectively reduce the production cost and cycle time of large structural components while ensuring the mechanical properties of the structure, this article proposes a novel three‐dimensional braided and prepreg‐layered (braid‐and‐lay) composite forming process that is studied in the context of metro bogies. First, the performance advantages of braid‐and‐lay composites were verified through experimental methods. Then, a multi‐scale analysis method, combining experimental and finite element analysis, accurately predicted the macroscopic elastic parameters of the three‐dimensional braided composite with an error of less than 10% compared to the experimental values. Finally, a structural optimization design of the braid‐and‐lay composite metro bogie was carried out based on the predicted elastic parameters. The results show that the mass of the structure was reduced by 15.33%, from 272.103 to 230.386 kg, while ensuring that the displacement and stress responses do not exceed the constraint range.Highlights Proposed a braid‐and‐lay integrated composite forming process. A multi‐scale analysis method, combining experimental and finite element analysis, was used to predict the modulus. The effect of braiding parameters on modulus prediction was investigated. The influence of the forming process and structural parameters on the performance of the metro bogie was investigated. The lightweight design of the metro bogie is effectively realized.

Instant Noodle Production Information System Using The Method Supply Chain Management To Overcome Targets Not Achieved

Improvement This research aims to analyze and implement an instant noodle production information system using the Supply Chain Management (SCM) method to overcome the inability to achieve predetermined production targets. In this study, an analysis was carried out on the entire supply chain in the production of instant noodles, which includes raw material suppliers, production processes, distribution and sales. The research method used is a qualitative method. The subjects of this study were instant noodle company employees. The results showed that the application of a production information system using the SCM method could help companies increase the efficiency of instant noodle production. With an integrated information system, companies can gain better visibility on consumer demand, raw material inventory, and production status. This allows companies to carry out more accurate production planning, accelerate production cycle times, and optimize resource use

Sintering of Protonic Ceramics for Tubular Solid Oxide Fuel Cells

The fabrication of proton-conducting solid oxide fuel cells (PC-SOFCs) has been challenging mainly due to the poor sinterability of common proton-conducting electrolyte materials. Extremely high sintering temperatures (up to 1600 °C) and long sintering times (>10 h) are typical for obtaining dense, gas-tight proton-conducting electrolytes. Apart from the high energy cost and long production cycle time, the high sintering temperature leads to several other issues, including chemical stability of the electrolyte and its compatibility with the electrodes. In the present work, we focused on optimizing the co-sintering temperature of tubular PC-SOFCs using a freeze-cast anode support. The densification of the BaZr0.3Ce0.5Y0.2O3 (BZCY) electrolyte was greatly facilitated by the sintering shrinkage of the NiO-BZCY anode support, which was as high as 35%. Preliminary electrochemical testing of the fabricated cells was also conducted.

Reduction in Total Production Cycle Time by the Tool Holder for the Automated Cutting Insert Quick Exchange and by the Double Cutting Tool Holder

The time taken to exchange a cutting tool and the actual machining time are the components in a total production cycle time for a part, that affects productivity. Automated plate exchange systems strive for the simplest possible principles to achieve the shortest possible tool exchange time with sufficient accuracy. The tool holder in the presented article is based on the principle of a combination of translational, rotational movement, and stop surfaces by using a single pull–push rod for simple control. The article provides alternative tool holder designs and turning results of such holders using Rz-f dependence. The results of the time reduction are satisfactory and give a prerequisite for using a tool holder for the automated exchange of triangular cutting inserts. Moreover, the article provides the approach to reduce the mentioned total production cycle time by a reduction in the actual machining time for a part by use of tooltip radii, not by increasing the cutting speed. The triangular cutting insert can have three tooltips of three different tooltip radii for roughing and finishing. In addition, for reduction of the actual machining time, the double cutting tool with both the small tooltip radius for rouging and the large tooltip radius for finishing is presented. The double tool holders showed a 2.4-times reduction in the actual machining time for a part with Rz = 20 µm.

Joint decision-making of virtual module formation and scheduling considering queuing time

Formation and scheduling are the most important decisions in the virtual modular manufacturing system; however, the global performance optimization of the system may be sacrificed via the superposition of two independent decision-making results. The joint decision of formation and scheduling is very important for system design. Complex and discrete manufacturing enterprises such as shipbuilding and aerospace often comprise multiple tasks, processes, and parallel machines, resulting in complex routes. The queuing time of parts in front of machines may account for 90% of the production cycle time. This study established a weighted allocation model of a formation-scheduling joint decision problem considering queuing time in system. To solve this nondeterministic polynomial (NP) problem, an adaptive differential evolution-simulated annealing (ADE-SA) algorithm is proposed. Compared with the standard differential evolution (DE) algorithm, the adaptive mutation factor overcomes the disadvantage that the scale of DE’s differential vector is difficult to control. The selection strategy of the SA algorithm compensates for the deficiency that DE’s greedy strategy may fall into a local optimal solution. The comparison results of four algorithms of a series of random examples demonstrate that the overall performance of ADE-SA is superior to the genetic algorithm, and average iteration, maximum completion time, and move time are 24%, 11%, and 7% lower than the average of other three algorithms, respectively. The method can generate the joint decision-making scheme with better overall performance, and effectively identify production bottlenecks through quantitative analysis of queuing time.

Propagation of cacao (Theobroma cacao L.) clone ‘CCN51’ using somatic embryogenesis: from pilot scale to commercial production

ABSTRACT The transition of promising technologies for the massive production of cacao trees from research to commercial scale is often difficult and expensive. As a result, the timeframe estimated for plantlet production is underestimated resulting in exceptionally long processes in the laboratory that make the production system unfeasible to bring to markets. Somatic embryogenesis (SE) is considered the most suitable and integrated technology for the large-scale production of clonal cocoa plants, compared to conventional methods. To date, practical application of SE to produce cocoa genotypes of interest has been limited, and for ‘drop-in’ technology replacements, price is of paramount importance for success. Therefore, the objective of this work was to produce the CCN51 genotype in a pilot scale in the laboratory with an approach to commercial production. The productive stages for a complex biological process such as SE and a reduction in production cycle time were defined. The production stages defined for SE were initiation, multiplication, maturation, germination, and acclimatization. The minimal time obtained for CCN51 production was 8.3 months: 30, 70, 50, 70, and 30 days, respectively. The decrease in the time of the production process directly influences the process cost and it represents a breakthrough in the technology development.

Resilient Supply Chain Framework for Semiconductor Distribution and an Empirical Study of Demand Risk Inference

Supply chain uncertainty is high due to low information transparency in the upstream and downstream, long lead time for supply chain planning, short product life cycles, lengthy production cycle time, and continuous technology migration. The construction and innovation of the new program of supply the chain faces huge challenges. This study aims to propose a smart resilient supply chain framework with a decision-making schema through the plan-do-check-act management cycle. It can enhance supply chain resilience and strengthen industrial competitiveness. Moreover, an empirical study of demand forecast and risk inference for semiconductor distribution is conducted as a validation. Through demand pattern clustering and forecasting for historic customer order behaviors, the demand status of each customer is classified, and an optimal planning solution is released to support decision-making. The result has shown the practical viability of the proposed approach to drive collaborative efforts in enhancing demand risk management to improve supply chain resilience. The proposed forecast model performs better than all four benchmark models, and the revised recall of the proposed risk reference model shows high accuracy in all demand risk levels. As supply chain resilience is about to be reconstructed due to the industrial revolution, a government and industry alliance should follow the resilient supply chain blueprint to gradually make the manufacturing strategy a technology platform in the Industry 4.0 era.

Indicator analysis of the technological position of a manufacturing company

Abstract A turbulent manufacturing market, especially in the metal industry, determines the quality of products and the level of production efficiency, which contributes to a company's market position and competitiveness. The aim of the study was to develop a model to define a manufacturing company's current market position using KPIs in relation to a key product - gearbox casting. The company's position was defined in terms of the relationship occurring between technological capabilities and market position. An additional aim of the study was to identify critical determinants and, ultimately, to identify conditions for strengthening market position. As a test of the proposed model, the position of the analysed company (in terms of technological capabilities and market position) was defined as "Search for occasions" - box 9 within the 3×3 matrix. Technological determinants that weaken the company's position (low level of maintenance capacity and long production cycle time) and determinants with a strong negative impact on market position (low level of human resource development) were identified. An element of novelty is the use of KPIs as variables determining the position of the company within the 3×3 matrix, which is indicative of a specific technological position in the market. Further lines of research will concern the determination of appropriate KPIs in relation to the identified critical areas of the company. Subsequent steps will concern the implications of the model in relation to the company's other key aluminium alloy castings.

Optimal Process Planning for Hybrid Additive and Subtractive Manufacturing

AbstractHybrid manufacturing technology has enabled manufacturers to combine advantages of mainly subtractive and additive manufacturing technologies. A single machine supports producing products with complex geometry, at high quality, and with a high degree of automation. To benefit from these advantages, decisions taken in the process planning stage of such a sophisticated manufacturing system should be optimized. The objective of this paper is to determine the optimal process plan considering both the engineering and manufacturing aspects of the hybrid technology. A comprehensive process planning model is proposed. The model specifies the optimal sequence of additive and subtractive features that minimizes the production cycle time. In addition, the model sets the optimal part orientations such that the time needed for building support structures, performing post-processing and inspection operations, changing cutting tools and printing nozzles, and unclamping the part is minimized. The model is comprehensive as it considers productive and non-productive times, precedence, technological, quality, and manufacturing restrictions imposed on hybrid manufacturing systems. The proposed model is nonlinear; due to this nonlinearity, the model is intractable. A linearization scheme is applied to formulate an equivalent linear model that is solvable to optimality by commercial solvers. Case studies on test and industrial parts are provided to evaluate the computational performance of the proposed model. Integrating the proposed model in hybrid manufacturing (HM) systems ensures adopting the HM technology in its optimal direction. HM technology is an enabler of establishing a smart manufacturing system which is one of the pillars of Industry 4.0.

Marine Natural Gas Hydrate Self-Entry Exploitation Device: Evaluation of Production Enhancement Measures

Test exploitation equipment and technology have progressed considerably in marine natural gas hydrate (NGH) exploitation, but many critical technical issues still need to be resolved before commercial production. Previous studies have proposed a non-drilling exploitation device—a self-entry exploitation device (SEED)—but reaching the NGH commercial exploitation threshold in its initial state is difficult. Consequently, we verified and evaluated some production enhancement measures to improve the exploitation system of the SEED. In this study, based on the geological data from the SHSC-4 site in the Shenhu sea and the material characteristics of the SEED, we carried out four production enhancement measures by numerical simulation. The results indicate that: (i) open-hole position adjustment can expand the contact areas between the device and NGH reservoirs; (ii) the effect of inner wall heating is limited but sufficient to achieve the goal of preventing clogging; (iii) it is necessary to select a reasonable spacing according to a combination of expected production cycle time and pressure when carrying out clustered depressurization; and (vi) when performing depressurization combined with thermal stimulation exploitation, factors such as permeability and thermal conductivity play a decisive factor in gas production.

Wire-Feeding Based Additive Manufacturing of the Ti–6Al–4V Alloy. Part I. Microstructure

In recent years, metal additive manufacturing (AM), also known as 3D printing, is grown massively in the industry. The ability of AM to build parts directly from the digital representation makes it an excellent alternative compared to traditional manufacturing technologies, such as milling, welding, casting, rolling, stamping, forging and turning for rapidly making highly customized parts. Currently, a number of different powder- and wire-based AM technologies are developed for 3D printing of metals. A number of potential benefits of AM are noted, including the allowance of design freedom, complex parts’ production, the material waste and part weight reductions, material use minimization; it also saves the time and money of the production cycle times. Due to the feasibility of the economically producing large-scale metal components with relatively high deposition rate, low machinery cost, high material efficiency, and shortened lead time as compared to the powder-based AM, the wire-based AM significantly attracted in the industry and academia due to its ability to produce the large components of the medium geometric complexity. During this AM process, the wire is fed by the controlled rate into the melt pool produced by the electric arc, laser or electron beam as the heat source. In the past few decades, the basic research and development efforts are devoted to the wire-based 3D printing parts made of Ti–6Al–4V alloy, which has been widely investigated and used in different fields such as aerospace, automotive, energy, marine industries and in addition to the prosthetics and the orthopaedic implants. Numerous studies in recent years on the influence of the 3D printing parameters have shown a significant difference in the mechanism and kinetics of the microstructure formation in the Ti–6Al–4V alloy samples compared to traditional technologies. It is well investigated that the mechanical properties of such alloy are dependent on the solidification macro- and microstructure, which is controlled by the thermal conditions during 3D printing. In the present review, the main microstructural characteristics, which determine the mechanical properties of the two-phase Ti–6Al–4V alloy, are analysed for the samples obtained by wire-feed 3D printing with various sources used for the wire melting, namely, the electric arc, the laser, and the electron beam. At first, the review introduces the links between the process parameters, resultant microstructures, especially, the morphology, the size and the quantitative ratio of the α and β grains in the as-printed Ti–6Al–4V alloy samples. However, the metallic products manufactured by a vast majority of the AM processes need to be post-processed by heat treatment and/or hot isostatic pressing, which are also discussed in this review.

Feasibility of Digital Twins to Manage the Operational Risks in the Production of a Ready-Mix Concrete Plant

The ready-mix concrete supply chain is highly disruptive due to its product perishability and Just-in-Time (JIT) production style. A lack of technology makes the ready-mix concrete (RMC) industry suffer from frequent production failures, ultimately causing high customer dissatisfaction and loss of revenues. In this paper, we propose the first-ever digital twin (DT) system in the RMC industry that can serve as a decision support tool to manage production risk efficiently and effectively via predictive maintenance. This study focuses on the feasibility of digital twins for the RMC industry in three main areas holistically: (1) the technical feasibility of the digital twin system for ready-mix concrete plant production risk management; (2) the business value of the proposed product to the construction industry; (3) the challenges of implementation in the real-world RMC industry. The proposed digital twin system consists of three main phases: (1) an IoT system to get the real-time production cycle times; (2) a digital twin operational working model with descriptive analytics; (3) an advanced analytical dashboard with predictive analytics to make predictive maintenance decisions. Our proposed digital twin solution can provide efficient and interpretable predictive maintenance insights in real time based on anomaly detection, production bottleneck identification, process disruption forecast and cycle time analysis. Finally, this study emphasizes that state-of-the-art solutions such as digital twins can effectively manage the production risks of ready-mix concrete plants by automatically detecting and predicting the bottlenecks without waiting until a production failure happens to react.

Inflatable architecture. Short critical history of uses in architecture

The pandemic crisis, as a turning point in recent history, has caused existing resources to be mobilized in a short time and triggered the emergence of unique approaches to spatial reorganization. With their formal freedom, unlimited adaptability and short production cycle times, lightweight inflatable or pneumatic structures, which are still in the midst of a technological boom, are an undeniable source of inspiration for today's crisis adaptation. Beyond pragmatic features such as ergonomics, protection and cleanliness, a variety of stylistic approaches can be identified, ranging from small-scale, minimal interventions in interior architecture, to large-scale, urban interventions. The article reviews the sources of inspiration that cross time and space, moving from the utopias of the 1960s to the emergency projects of the 21st century, with the aim of highlighting, through the broad spectrum of solutions, a direction to follow in architecture adapted to crisis solutions. Inflatable structures still fascinate, having the potential to be symbolic in any context.

Applying Lean Six Sigma to improve garment production processes-A case study

The company under study specializes in producing garment products. The production process of the company has so much waste, a long production time, a high cycle time, and a high defect rate, leading to low productivity, low quality, and late deliveries, affecting the competitive edge of the company. In this article we have discussed how Six Sigma can be applied to improve the company production process to reduce waste, the process production lead time, the cycle time, and the process defect rate and then to improve productivity and quality and finally increase the on-time delivery rate and the competitive edge of the company. The research methodology is based on Lean Six Sigma theory, with the platform of DMAIC procedure, including five steps: define, measure, analyze, improve, and control. The tools used in the steps of DMAIC procedure include cause and effect diagram, Pareto diagram, value stream management, work design, SMED, line balancing, Kanban systems, FIFO, autonomous maintenance, visual management, design of experiments, and control charts. After applying Lean Six Sigma tools, the company has reduced the production lead time by 89.21% from 279 to 30.1 min, reduced the production cycle time by 36% from 25 to 16 s, reduced the process defect rate by 37.45% from 14.9 to 9.32%, and then improved the on-time delivery rate.

Alati "unapređenja" i "kontrole" u montaži mikro komponenti - studija slučaja

The process of assembling micro components requires careful planning where precise and reliable data collecting is necessary due to a short production cycle time. After determining the shortages of the current data monitoring system, in this paper, by using the "Improve" and "Control" phases of DMAIC cycle, the development and later testing of a new tool for automatic capture and analysis of data obtained from the machine was done. SWOT analysis was used to establish the production site's and current manufacturing execution system strengths and weaknesses, opportunities and threats, which were then utilized to create the newly developed solution accurate and feasible. A tool calibration data was obtained on 9 machines in automotive company's micro component assembly unit. To confirm the accuracy of the data, a RunAtRate test was done on the machines, and by using hypothesis testing, the initial reliability of the new solution was determined. Further testing and comparison revealed that the newly proposed tool recorded 73-80% greater downtime and 40-50% more defective parts than the previously installed system. Accordingly, the usefulness of the proposed Lean Six SIGMA tool is confirmed, and for periodic accuracy checks and further improvement, it is necessary to apply the PDCA cycle.

Sustainable Production-Inventory Model with Multi-Material, Quality Degradation, and Probabilistic Demand: From Bibliometric Analysis to A Robust Model

An adequate sustainable production inventory model is expected to represent complex real-life cases involving fuel, emissions, and electricity costs as well as multi-materials, quality degradation, and probabilistic demand. Therefore, this study was conducted to develop this kind of model to determine the number of raw material shipments (), production cycle time (), and the number of finished goods delivered (n) to maximize the Expected Total Profit (ETP). The proposed model is based on a bibliometric literature analysis of the sustainable production-inventory problem which is visualized using the VOSviewer. Moreover, a sophisticated Harris-Hawks Optimization (HHO) algorithm was proposed to solve the problems identified in the sustainable production inventory model optimization. It is also important to note that three numerical cases were provided to evaluate the performance of the algorithm. The findings showed that the suggested HHO method outperforms the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in maximizing ETP and this means it is better for ETP optimization. It was also discovered from the sensitivity analysis that an increase in the rate of quality degradation (k) led to a reduction in both the ETP and T.

An efficient sustainable smart approach to biofuel production with emphasizing the environmental and energy aspects

By using renewable biomass, the advancement in biofuel production through a smart inspection production framework is a crucial substitute to fossil fuels which support minimizing environmental pollution and zero carbon emissions. Traditional biofuel production can be converted into a sustainable smart production system by utilizing smart machines, skilled labor, and reduced energy consumption. The prime purpose of this study is to produce pure biofuel with less energy consumption and carbon emissions through a smart production framework of biofuel. The work-in-process inventory is calculated for different costs, including air handling, lighting, and carbon emissions, in each stage of the study. Although smart variable production is utilized, still impure biofuel is produced with a random production rate. The impure biofuel is purified to make it pure. A multi-delivery technique is used such that a fixed amount of biofuel of n segments of the pure biofuel is transported to the market as per the market’s demand. The total profit of this study is maximized globally with the help of the classical optimization technique. Four numerical examples are observed to validate the model. The applicability and efficiency of the proposed model are finally demonstrated through a real case study in India. Two special cases prove the necessity of smart production and discrete investment for setup cost reduction. The sensitivity analysis and the graphical representation give each parameter’s effect on the model’s total profit. Numerical results prove that if no discrete investment for setup cost reduction and fixed production rate is taken, the common production cycle time is increased remarkably. It is seen that the total profit of this study rises 4.30% from the traditional production system. Moreover, numerical results prove a major effect on renewable energy in a sustainable smart production system.

Integrated maintenance, inventory and quality engineering decisions for multi-product systems

Abstract It is essential for manufacturers to consider the interrelation among quality, inventory, and maintenance decisions to detect imperfect quality products, keep the production system in good operating condition, and manage quality and inventory costs. Hence, this paper aims to develop an integrated model of inventory planning, quality engineering, and maintenance scheduling in which the expected total cost per time unit is minimised by determining the sample size, sampling interval, control limit coefficient, along with production cycle time. In this regard, an imperfect multi-product manufacturing system is considered, in which the inventory shortage in satisfying the demand for each product type and the idle time during the production cycle are not allowed. It is assumed that the process starts in an in-control condition where most produced units are conforming. However, due to the occurrence of an assignable cause (AC), the process mean moves to an out-of-control condition in which a significant fraction of non-conforming units is produced. The efficiency of the proposed mathematical model is evaluated by a numerical example, and then the sensitivity of the proposed model to important inputs is analysed. Finally, a comparative study based on the Taguchi design approach is given to confirm the capability of the proposed model to achieve remarkable cost savings.

Комплексная цифровизация, реализуемая при освоении запасов Гремячинского месторождения калийно-магниевых солей

The paper reviews the main trends in digitalization of the production processes implemented during the development of the Gremyachinskoe potassium-magnesium salt deposit. The main objective of the digital projects is to maintain competitiveness in the current market conditions. When implementing the integrated digital transformation project, the EuroChem-VolgaKaliy created a clear system of criteria to control the efficiency of the business processes and intriduced instrumental control over the actual duration of the technological cycle. Comparing more complete information on personnel with production metrics data creates objective ratings of face teams and foremen, which makes it possible to reduce production cycle time and increase average daily production volumes by 26%. An important area for further implementation of the project will be upgrading the IT-infrastructure, robotization of the office tasks, e.g. automatic generation of production requests, transfer of messages between the related divisions with no manual entry of information. After the information array is formed, it is planned to introduce the dependency analysis of production indicators with definition of equipment breakdown parameters. This will help to reduce the total number of downtime cases and increase the productivity of the mine as a whole, and will ensure a significant reduction in duration of unscheduled emergency repairs. A promising trend in activities of the Gremyachinskoe mining-and-processing integrated works is application of artificial intelligence in planning of mining operations. In order to solve these tasks it is envisaged to create 3D models, to simulate various methods and technologies of mining salt formations, to determine the design parameters of the mining method with account of the actual morphology and thixotropy of the formations.