Showing papers in "Advances in Production Engineering & Management in 2021"
TL;DR: In this paper, the authors constructed a closed-loop supply chain material flow and capital flow coupling system composed of manufacturers, sellers, and recyclers to explore the impact of material flow sudden interruption on the closed loop supply chain system when an uncertain emergency occurs.
Abstract: The complex and changeable external social and economic environment has a significant impact on the sustainable development of the closed-loop supply chain In particular, the occurrence of uncertain emergencies increases the risk of interruption of the closed-loop supply chain, making it insufficient to analyze its complex changes from the perspective of material flow alone Based on this analysis, the paper constructs a closed-loop supply chain material flow and capital flow coupling system composed of manufacturers, sellers and recyclers to explore the impact of material flow sudden interruption on the closed-loop supply chain system when an uncertain emergency occurs In this paper, based on the closed-loop supply chain system coupled with logistics and capital flow, a system dynamics simulation model was established by using Vensim simulation software to analyze the impact of COVID-19 epidemic on manufacturers, sellers and recyclers under five scenarios The results show that when COVID-19 outbreaks occur, the material flow of each main enterprise in the closed-loop supply chain is more easily influenced than the capital flow At the same time, it can be found that the recyclers in the main enterprises of the closed-loop supply chain are more easily influenced by the material flow The model constructed in this paper has applicability and can be used for related studies of closed-loop supply chain under other emergencies, but the scene design should be carried out according to the characteristics of emergencies themselves © 2021 Production Engineering Institute All rights reserved
19 citations
TL;DR: A dynamic job‐shop scheduling model based on deep learning neural networks and the improved multi‐objective genetic algorithm (MOGA) was proposed, which effectively reduces the cost of manpower and materials and enhances the core com‐ petitiveness of the manufacturer.
Abstract: Ideally, the solution to job‐shop scheduling problem (JSP) should effectively reduce the cost of manpower and materials, thereby enhancing the core com‐ petitiveness of the manufacturer. Deep learning (DL) neural networks have certain advantages in handling complex dynamic JSPs with a massive amount of historical data. Therefore, this paper proposes a dynamic job‐shop schedul‐ ing model based on DL. Firstly, a data prediction model was established for dynamic job‐shop scheduling, with long short‐term memory network (LSTM) as the basis; the Dropout technology and adaptive moment estimation (AD‐ AM) were introduced to enhance the generalization ability and prediction effect of the model. Next, the dynamic JSP was described in details, and three objective functions, namely, maximum makespan, total device load, and key device load, were chosen for optimization. Finally, the multi‐objective prob‐ lem of dynamic JSP scheduling was solved by the improved multi‐objective genetic algorithm (MOGA). The effectiveness of the algorithm was proved experimentally.
14 citations
TL;DR: The AM4.0CARD approach as discussed by the authors is a new management approach based on additive manufacturing (AM) technologies and good practice, which is proposed in order to gain a competitive advantage through the implementation and use of AM technologies.
Abstract: Nowadays, it is necessary to formulate and implement a development strate‐ gy in manufacturing enterprises, in line with the assumptions of the Industry 4.0 concept. In this context, a gap in the research has been observed in effec‐ tive management methods, in order to gain a competitive advantage through the implementation and use of Additive Manufacturing (AM) technologies. The main purpose of the study is to build a new approach to management, based on the implementation of new AM technologies and good practice. This paper uses the detailed literature studies and results from the empirical re‐ search of some 250 Polish manufacturing enterprises; this material contains a sample thereof, processed into a new approach. The major contributions of the work are as follows: (1) identification of current management areas in which manufacturing companies focus their activities, in the context of Indus‐ try 4.0, (2) the establishment of the correlation between gaining a competitive advantage and implementing AM technologies in the context of Industry 4.0, (3) Defining the so‐called AM4.0CARD as a new management approach, based on AM technologies and the requirements of Industry 4.0. Managers of manu‐ facturing enterprises, thanks to the use of the proposed approach, may take a strategic decision, regarding the implementation of AM technologies, due to the possibility of forecasting the impact of such an investment on the im‐ provement of the company's competitive advantage.
13 citations
TL;DR: This paper constructed the multi-objective relationship of the disassembly line balance problem, which belongs to the NP-hard problem, and the intelligent optimization algorithm shows excellent performance in solving this problem.
Abstract: Disassembly activities take place in various recovery operations including remanufacturing, recycling, and disposal. Product disassembly is an effective way to recycle waste products, and it is a necessary condition to make the product life cycle complete. According to the characteristics of the product disassembly line, based on minimizing the number of workstations and balancing the idle time in the station, the harmful index, the demand index, and the number of direction changes are proposed as new optimization objectives. So based on the analysis of the traditional genetic algorithm into the precocious phenomenon, this paper constructed the multi-objective relationship of the disassembly line balance problem. The disassembly line balance problem belongs to the NP-hard problem, and the intelligent optimization algorithm shows excellent performance in solving this problem. Considering the characteristics of the traditional method solving the multi-objective disassembly line balance problem that the solution result was single and could not meet many objectives of balance, a multi-objective improved genetic algorithm was proposed to solve the model. The algorithm speeds up the convergence speed of the algorithm. Based on the example of the basic disassembly task, by comparing with the existing single objective heuristic algorithm, the multi-objective improved genetic algorithm was verified to be effective and feasible, and it was applied to the actual disassembly example to obtain the balance optimization scheme. Two case studies are given: a disassembly process of the automobile engine and a disassembly of the computer components.
10 citations
TL;DR: In this article, the authors propose a new collaboration model between the OEM and its suppliers, since OEMs need to collaborate directly with suppliers of lower levels of the value chain in order to facilitate the standardisation of components and modules across different products.
Abstract: Generating economies of scale is one of the most desirable goals when devel‐ oping modular product systems. Since complex products are commonly de‐ veloped in collaboration between an Original Equipment Manufacturer (OEM) and its suppliers, pursuing this goal inherently establishes interdependencies between the development process, supplier integration and supply chain design. To fully reap the benefits of modular product systems requires a com‐ prehensive approach that encompasses these fields and addresses the inter‐ dependencies between them via a coherent collaboration between develop‐ ment and purchasing. This is the main focus of this work. In this paper, we first describe how the product development process has to be restructured for the concerted development of modules and overall products within the scope of a modular product system. Secondly, we propose a new collaboration model between the OEM and its suppliers, since OEMs need to collaborate directly with suppliers of lower levels of the value chain in order to facilitate the standardisation of components and modules across different products. Finally, we delineate an awarding process for both development services and production volumes for series supply that resolves the conflicting priorities of economies of scale and avoiding over‐dependence on single suppliers. The process models described in this paper have been conceived based on sys‐ tems engineering principles and have been successfully tested and further refined throughout several industrial projects carried out with two automo‐ tive manufacturers. The resulting approach will be demonstrated using a generic example taken from the automotive industry.
10 citations
TL;DR: A scenario-based robust optimization method is used to deal with uncertain parameters such as the demand of new products, the return rates of returned products and the sale prices of remanufactured products and shows a robust optimal resource allocation solution that considers multiple scenarios.
Abstract: Green closed-loop supply chain management is an important topic for business operations today because of increasing resource scarcity and environmental issues. Companies not only have to meet environmental regulations, but also must ensure high quality supply chain operation as a means to secure competitive advantages and increase profits. This study proposes a multi-objective mixed integer programming model for an integrated green closed-loop supply chain network designed to maximize profit, amicable production level (environmentally friendly materials and clean technology usage), and quality level. A scenario-based robust optimization method is used to deal with uncertain parameters such as the demand of new products, the return rates of returned products and the sale prices of remanufactured products. The proposed model is applied to a real industry case example of a manufacturing company to illustrate the applicability of the proposed model. The result shows a robust optimal resource allocation solution that considers multiple scenarios. This study can be a reference for closed-loop supply chain related academic research and also can be used to guide the development of a green closed-loop supply chain model for better decision making.
8 citations
TL;DR: A material handling system of smart electrical connectors workshop was discussed to verify the scheduling model and the speed control strategy combined with the MapReduce framework is feasible and effective to reduce the AGV path conflict probability.
Abstract: During material handling processes, automated guided vehicles (AGVs) pose a path conflict problem. To solve this problem, we proposed a multi-objective scheduling model based on total driving distance and waiting time, and used the A* path planning algorithm to search the shortest path of AGV. By using a speed control strategy, we were able to detect the overlap path and the conflict time. Additionally, we adopted an efficient MapReduce framework to improve the speed control strategy execution efficiency. At last, a material handling system of smart electrical connectors workshop was discussed to verify the scheduling model and the speed control strategy combined with the MapReduce framework is feasible and effective to reduce the AGV path conflict probability. The material handling system could be applied in workshop to replace manual handling and to improve production efficiency.
8 citations
TL;DR: By combining agile and traditional project management approaches, organizations can take advantage of some benefits of agile devel‐ opment without abandoning the stability provided by a traditional approach.
Abstract: Aligning the project management approach to a particular project is consid‐ ered to be essential for project success. Based on the literature review, in this research, the project management approach is analyzed through differentia‐ tion between agile and traditional approaches within the specific managerial aspects. This research aimed to contrast these two project management ap‐ proaches and explore their impact on different project success dimensions. The research was conducted on a sample of 227 project management profes‐ sionals worldwide, using the PLS‐SEM method. Research results denounced that, in most cases, the traditional approach is applied in project initiation and planning. It has proven to provide higher‐level od project success, while, within all other managerial aspects considered in this research, they gravitate more towards the agile approach. By combining agile and traditional ap‐ proaches, organizations can take advantage of some benefits of agile devel‐ opment without abandoning the stability provided by a traditional approach. The study is relevant for project management practitioners tailoring down the success‐oriented project management approach and developing project man‐ agement contingency theory for academics.
7 citations
TL;DR: In this paper, a general framework for sustaining an effective assessment methodology for small and medium-sized enterprises (SMEs) is proposed. But, the model does not consider the economic aspects of the enterprises.
Abstract: Small and Medium‐Sized Enterprises (SMEs) are of major importance to de‐ veloping countries. SMEs are the main drivers to strengthen society in sus‐ taining economic growth and development. Governments provide various support programs to improve their industrial power and to increase the number of enterprises in the market. The enterprises must be assessed and suitable funds should be provided to those in need, to achieve an effective support program in the most efficient way.This requires implementing an assessment methodology based on a predefined set of scientific criteria. The current literature is comprehensive enough to assess the healthiness of the enterprises concerning strategic, technologic, financial as well as intellectual competencies but on the other hand, it lacks of an assessment model. This study aims to introduce a general framework for sustaining an effective as‐ sessment methodology for SMEs to eliminate this gap. The proposed model measures five different types of competencies such as Technological Compe‐ tency, Strategic Competency, Financial Competency, Intellectual Competency, R&D and Innovation Competency. These competencies are to put forth the conditions in which the enterprises are running accurately. A real‐life case study is conducted to ensure the baseline of the model to be implemented. The governmental organizations may utilize the model for sustaining their support role effectively to SMEs.
4 citations
TL;DR: This research breaks through the realistic situation of straight aisle leading warehouse layout, and enriches the relevant layout theory, and believes that the layout of non-rectangular complex special-shaped warehouses based on curve trajectory aisles would become an important research topic.
Abstract: Refined layout is a basis of warehousing efficiency. Straight aisle is a typical feature of current warehouse internal layouts. The purpose of this paper is to explore the possibility of using curve aisles for warehouse layout. By Choosing typical non-traditional layouts and transforming their inclined cross-aisle trajectory into parabola, two parabolic aisle layouts, parabolic Flying-V and parabolic Fishbone, are constructed. For unit-load warehouses, based on the morphological characteristic analysis and the parabolic types selection, the picking distance model and the cross-aisle length formula are presented. Interval Numerical Simulation Method (INSM) and Genetic Algorithms (GA) are adopted to solve the model respectively in order to verify the results. This research breaks through the realistic situation of straight aisle leading warehouse layout, and enriches the relevant layout theory. The calculation results of 100 warehouses with different sizes show that the picking distance of parabolic Flying-V could be reduced by 0.22-0.62 % compared with the straight layout, and the theoretical possible improvement space has been compressed by 2.42-12.26 %. Its length of cross-aisle is shortened by -0.03-3.10 %. The picking distance of parabolic Fishbone could be only reduced by 0.02-0.04 %. The theoretical possible improvement space has been compressed by 1.27-1.83 %. But its length of cross-aisle will increase by 4.63-19.50 % significantly. We believe that the layout of non-rectangular complex special-shaped warehouses based on curve trajectory aisles would become an important research topic. In addition, after some necessary modifications to the objectives and constraints, the proposed method in this paper may also be used for the arrangement of machines and devices in a workshop in principle.
3 citations
TL;DR: An improved genetic algorithm (VNS-GA) that uses polar coordinate classification to generate the initial solutions is proposed and integrates the variable neighbourhood algorithm to solve the multiple objective optimization of the mTSP with workload balance.
Abstract: The multiple traveling salesman problem (mTSP) is an extension of the traveling salesman problem (TSP), which has wider applications in real life than the traveling salesman problem such as transportation and delivery, task allocation, etc. In this paper, an improved genetic algorithm (VNS-GA) that uses polar coordinate classification to generate the initial solutions is proposed. It integrates the variable neighbourhood algorithm to solve the multiple objective optimization of the mTSP with workload balance. Aiming to workload balance, the first design of this paper is about generating initial solutions based on the polar coordinate classification. Then a distance comparison insertion operator is designed as a neighbourhood action for allocating paths in a targeted manner. Finally, the neighbourhood descent process in the variable neighbourhood algorithm is fused into the genetic algorithm for the expansion of search space. The improved algorithm is tested on the TSPLIB standard data set and compared with other genetic algorithms. The results show that the improved genetic algorithm can increase computational efficiency and obtain a better solution for workload balance and this algorithm has wild applications in real life such as multiple robots task allocation, school bus routing problem and other optimization problems.
TL;DR: It has been found that the Rao algorithm performs better than the Jaya algorithm for optimization, and both the optimization algorithms results in considerable improvement in the SI of the machined surface.
Abstract: Advanced modeling and optimization techniques are imperative today to deal with complex machining processes like electric discharge machining (EDM). In the present research, Titanium alloy has been machined by considering different electrical input parameters to evaluate one of the important surface integrity (SI) parameter that is surface roughness Ra. Firstly, the response surface methodology (RSM) has been adopted for experimental design and for generating training data set. The artificial neural network (ANN) model has been developed and optimized for Ra with the same training data set. Finally, an adaptive neuro-fuzzy inference system (ANFIS) model has been developed for Ra. Optimization of the developed ANFIS model has been done by applying the latest optimization techniques Rao algorithm and the Jaya algorithm. Different statistical parameters such as the mean square error (MSE), the mean absolute error (MAE), the root mean square error (RMSE), the mean bias error (MBE) and the mean absolute percentage error (MAPE) elucidate that the ANFIS model is better than the ANN model. Both the optimization algorithms results in considerable improvement in the SI of the machined surface. Comparing the Rao algorithm and Jaya algorithm for optimization, it has been found that the Rao algorithm performs better than the Jaya algorithm.
TL;DR: In this article, a simple mathematical model of the box-house prototypes is developed using a fictive diagonal element for simulating the racking stiffness of the bracing timberglass wall element.
Abstract: Combining timber and glass in the wall elements of the building envelope with the proper orientation of such transparent façade elements enables the utilization of solar energy for heating and internal illumination of the building. However, the asymmetrical layout of timber‐glass wall elements in such buildings can result in problems with the horizontal stability of the structure, so their participation to load‐bearing capacity of the structure is usually ne‐ glected. The study deals with solutions for such elements as horizontal load‐ bearing members with proper connection details. First, specifically developed timber‐glass wall elements were experimentally tested under monotonic and cyclic horizontal point load, and further in combination with classical timber‐ framed wall elements implemented into special single and two‐storey box‐ house models, which were further experimentally tested on the shaking table. In the second part as the main goal of the study, a quite simple mathematical model of the box‐house prototypes is developed using a fictive diagonal ele‐ ment for simulating the racking stiffness of the bracing timber‐glass wall element. The calculated results for the 1st vibration period are compared with the previously measured experimental results to prove an accuracy of the developed model. Finally, a linear time‐history calculation is done as a sample presentation of the developed mathematical model using Landers accelera‐ tion spectrum. The developed mathematical model enables a simple and effec‐ tive seismic response calculation of timber buildings considering the devel‐ oped timber‐glass wall elements as load‐bearing bracing elements against horizontal load actions. The model can also be recommended for using in further parametric numerical academic studies analysing the influence of various parameters.
TL;DR: Wang et al. as mentioned in this paper put forward several basic distribution models and analyzes them in combination with practical applications, which has strong practical significance, and draw the conclusion that Chaopi Trading Co., Ltd. is a joint distribution system optimization business model.
Abstract: Joint distribution means multiple clients were provided distribution services together by only one third-party logistics company. It is a unified plan and implementation used in distribution centres and a distribution activity implemented by multiple consortia. Many problems in distribution can be solved through the joint use of distribution warehouse, vehicles and reasonable logistics business, so as to optimize the overall logistics node and route arrangement. This paper mainly discusses the model of joint distribution of fast moving consumer goods, proposes three types of the optimization model of joint distribution system with Chaopi as an example. We draw the conclusion that Chaopi Trading Co., Ltd. is a joint distribution system optimization business model. This paper puts forward several basic distribution models and analyzes them in combination with practical applications, which has strong practical significance. Although the development of public distribution in China is not very fast, it is an inevitable trend. Through the efforts and explorations of the governments of various countries, there will be more and more choices of public distribution models.
TL;DR: In this article, the linear combination of BWM and Gini coefficient method is used to improve the three-parameter interval grey number correlation model, which is applied to the impact evaluation of complex product engineering change.
Abstract: Change impact evaluation of complex product plays an important role in controlling change cost and improving change efficiency of engineering change enterprises. In order to improve the accuracy of engineering change impact evaluation, this paper introduces three-parameter interval grey number to evaluate complex products according to the data characteristics. The linear combination of BWM and Gini coefficient method is used to improve the three-parameter interval grey number correlation model. It is applied to the impact evaluation of complex product engineering change. This paper firstly constructs a multi-stage complex network for complex product engineering change. Then the engineering change impact evaluation index system is determined. Finally, a case analysis was carried out with the permanent magnet synchronous centrifugal compressor in a large permanent magnet synchronous centrifugal unit to verify the effectiveness of the proposed method.
TL;DR: In this article, the arithmetic mean absolute roughness and total height of profile (Rt) of spherical surface during finish turning of a commercial brass alloy CuZn40Pb2 were modeled using Response Surface Methodology (RSM).
Abstract: Surface roughness is one of the most significant factors to indicate the prod- uct quality. Diamond turning is an efficient and highly accurate material re- moval process to improve the surface quality of the workpiece. In the present study, the arithmetic mean absolute roughness (Ra) and total height of profile (Rt) of spherical surface during finish turning of a commercial brass alloy CuZn40Pb2 were modeled using Response Surface Methodology (RSM). The experimental investigations were carried out using the Central Composite Design (CCD) under dry conditions. The effect of cutting parameters such as spindle speed, feed rate and depth of cut) on spherical surface quality was analyzed using analysis of variance (ANOVA). A cuckoo search (CS) algorithm was used to determine the optimum machining parameters to minimize the surface roughness. Finally, confirmation experiments were carried out to verify the adequacy of the considered optimization algorithm.
TL;DR: In this paper, the effect of drill bit wear on the bone temperature rise through the internal gas cooling method via CO2 and to reduce the risk of incidence of thermal necrosis was investigated.
Abstract: Bone drilling is a major stage in immobilization of the fracture site. During bone drilling operations, the temperature may exceed the allowable limit of 47 °C, causing irrecoverable damages of thermal necrosis and seriously threatening the fracture treatment. One of the parameters affecting the temperature rise of the drilling site is the frequency of applying the drill bit and its extent of wear. The present study attempted to mitigate the effect of drill bit wear on the bone temperature rise through the internal gas cooling method via CO2 and to reduce the risk of incidence of thermal necrosis. To this end, drilling tests were conducted at three rotational speeds 1000, 2000, and 3000 r·min-1 in two states of without cooling and with internal gas cooling by CO2 through an internal coolant carbide drill bit, along with six drill bit states (new, used 10, 20, 30, 40, and 50 times) on a bovine femur bone. The results indicated that in the internal gas cooling state, as the number of drill bit applications increased from the new state to more than 50 times, the temperature of the hole site increased on average by ΔT = 2-3 °C (n = 1000 r·min-1), ΔT = 5-8 °C (n = 2000 r·min-1), and ΔT = 5-7 °C (n = 3000 r·min-1). Furthermore, the internal gas cooling method was able to significantly reduce the effect of the drill bit wear on the temperature rise of the drilling site and to resolve the risk of incidence of thermal necrosis regardless of the process parameters for drilling operations.
TL;DR: Fuzzy theory, Logit model and VSM are combined to salve the problem of manufacturing base location and suggest the optimal manu‐ facturing base from multiple candidate manufacturing bases with regard to less costs, shorter lead times, better manufacturing capabilities, better service benefits.
Abstract: Improving customer satisfaction and shortening the manufacturing cycle have become common concerns of current manufacturers. This paper presents a multi‐objective location model considering the maximization of collaborative manufacturing capabilities and service benefits. This method first uses the two dimensions of customer share and market consumption to segment cus‐ tomers, and identify the weight of various customer groups. Secondly, the space vector model (VSM) is used to calculate the matching between manu‐ facturing capabilities and manufacturing requirements. Then build a multi‐ objective location model based on the two goals of collaborative manufactur‐ ing capabilities and service benefits. Finally, the model was tested with simu‐ lation data, which proved the validity and feasibility of the model. According to the simulation results, managers can accurately select the optimal manu‐ facturing base from multiple candidate manufacturing bases with regard to less costs, shorter lead times, better manufacturing capabilities, better service benefits. In this paper, Fuzzy theory, Logit model and VSM are combined to salve the problem of manufacturing base location. Considering resources and service benefits of each manufacturing base, it is helpful to optimize the loca‐ tion of enterprises. From the academic and practical points, this study pro‐ vides a new perspective for the location problem.