Pub Date : 2022-08-27DOI: 10.1177/1063293x221121816
In the current digital era, the data captured during a product development process will grow from a large set of existing data sources to a new set of intermediate big data in every stream from product requirements, to conceptual design into manusfctutring details. In order to process the big set of product and process data and to extract the necessary knowledge from the intermediate set of new data, it is necessary to employ the modern computing facilities, such as Artificial Intelligence (AI) schemes, knowledge discovery, machine-learning procedures and deep-learning procedures. Further, efficient handling of the digital data using the traditional approaches is tedious and time consuming. Hence, various computing procedures and facilities need to be combined with concurrent product development process and tools to handle the processing of the big data in an efficient manner. This Special Issue (SI) aims to collect the cutting edge research works related to recent advancements in the applications of AI and its associated knowledge discovery schemes from various domains, such as design, engineering, manufacturing, quality, industrial and from various industries such as business, consumer, aerospace, defense, automotive, transportation, energy, life sciences, and medical fields. Authors are encouraged to submit their extended version of the research works to be presented in “International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering”, aka ICECONF 2023 to be held in Chennai India from Jan 5–7, 2023 for this special issue. The topic of interest of the SI includes;
{"title":"Special issue on “Artificial Intelligence and Knowledge Discovery in Concurrent Engineering”","authors":"","doi":"10.1177/1063293x221121816","DOIUrl":"https://doi.org/10.1177/1063293x221121816","url":null,"abstract":"In the current digital era, the data captured during a product development process will grow from a large set of existing data sources to a new set of intermediate big data in every stream from product requirements, to conceptual design into manusfctutring details. In order to process the big set of product and process data and to extract the necessary knowledge from the intermediate set of new data, it is necessary to employ the modern computing facilities, such as Artificial Intelligence (AI) schemes, knowledge discovery, machine-learning procedures and deep-learning procedures. Further, efficient handling of the digital data using the traditional approaches is tedious and time consuming. Hence, various computing procedures and facilities need to be combined with concurrent product development process and tools to handle the processing of the big data in an efficient manner. This Special Issue (SI) aims to collect the cutting edge research works related to recent advancements in the applications of AI and its associated knowledge discovery schemes from various domains, such as design, engineering, manufacturing, quality, industrial and from various industries such as business, consumer, aerospace, defense, automotive, transportation, energy, life sciences, and medical fields. Authors are encouraged to submit their extended version of the research works to be presented in “International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering”, aka ICECONF 2023 to be held in Chennai India from Jan 5–7, 2023 for this special issue. The topic of interest of the SI includes;","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"21 1","pages":"309 - 311"},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76524657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-23DOI: 10.1177/1063293X221118356
F. Trapsilawati, Subagyo, Dimas Ardy Firmansyah, N. Masruroh, I. B. Dharma, B. Wibowo
Small-medium enterprises (SMEs) have the potentials to translate ideas into innovative products in a quick and efficient manner. Therefore, they should be supported to transform into well-established companies. However, SMEs often lack knowledge regarding operation and management. This study proposes three-dimensional concurrent engineering (3DCE) approach to help SMEs accelerate their growth through differentiation and efficiency, leading to high-quality yet low-cost products with efficient delivery. This study aimed to develop a strategic formulation framework incorporating the 3DCE concept in product functionality, concurrent process design, and appropriate supply chain solutions. The framework has been developed and implemented in food and beverage SME. Strategy development follows the traditional approach, including environmental analysis, strategy formulation, and strategy mapping. However, the result of environmental analysis extracted in the form of SWOT and Grand Strategy matrices are specifically piled into concurrent strategic theme covering the concurrent product, process, and supply chain aspects. Predominantly, product features covering the product innovation and functionality and process features covering segmentation-based and cross-functional process designs were tailored with innovative supply chain solutions based on the segmented model. The detailed framework and its implementation are highlighted accordingly.
{"title":"Concurrent product-process-supply chain strategy formulation for small medium enterprises","authors":"F. Trapsilawati, Subagyo, Dimas Ardy Firmansyah, N. Masruroh, I. B. Dharma, B. Wibowo","doi":"10.1177/1063293X221118356","DOIUrl":"https://doi.org/10.1177/1063293X221118356","url":null,"abstract":"Small-medium enterprises (SMEs) have the potentials to translate ideas into innovative products in a quick and efficient manner. Therefore, they should be supported to transform into well-established companies. However, SMEs often lack knowledge regarding operation and management. This study proposes three-dimensional concurrent engineering (3DCE) approach to help SMEs accelerate their growth through differentiation and efficiency, leading to high-quality yet low-cost products with efficient delivery. This study aimed to develop a strategic formulation framework incorporating the 3DCE concept in product functionality, concurrent process design, and appropriate supply chain solutions. The framework has been developed and implemented in food and beverage SME. Strategy development follows the traditional approach, including environmental analysis, strategy formulation, and strategy mapping. However, the result of environmental analysis extracted in the form of SWOT and Grand Strategy matrices are specifically piled into concurrent strategic theme covering the concurrent product, process, and supply chain aspects. Predominantly, product features covering the product innovation and functionality and process features covering segmentation-based and cross-functional process designs were tailored with innovative supply chain solutions based on the segmented model. The detailed framework and its implementation are highlighted accordingly.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"13 1","pages":"411 - 423"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84988644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-23DOI: 10.1177/1063293X221120072
Shuai Zhang, H. Xu, Hua Zhang, Sihan Yang
Remanufacturing has become a Frontier technology in sustainable manufacturing and enables end-of-life products to be restored to their new conditions. Although remanufacturing scheduling has been widely investigated, the relationship between remanufacturers and customers is rarely examined. Therefore, a new game-relationship-based remanufacturing scheduling model with sequence-dependent setup times is proposed herein. In the model, the relationship between the remanufacturer and customers is constructed as a non-cooperative game, and the interval due dates are set based on the uncertain product quality to achieve effective remanufacturing and improve customer satisfaction. Multiple remanufacturing lines differentiated based on the quality grade of products are integrated into the proposed model. In addition, sequence-dependent setup times are considered in the model, which depend on the similarity between two adjacent tasks processed on a reprocessing unit. An improved discrete particle swarm optimization algorithm is proposed to obtain Nash equilibrium solutions via an efficient global search structure and a local search strategy. The algorithm is embedded with the Nash equilibrium solution evaluation method and integrated with multiple genetic operators to update the particles. The performance of the proposed algorithm in solving the proposed model is verified via a comparison with three baseline algorithms for managing different problem instances.
{"title":"Game-relationship-based remanufacturing scheduling model with sequence-dependent setup times using improved discrete particle swarm optimization algorithm","authors":"Shuai Zhang, H. Xu, Hua Zhang, Sihan Yang","doi":"10.1177/1063293X221120072","DOIUrl":"https://doi.org/10.1177/1063293X221120072","url":null,"abstract":"Remanufacturing has become a Frontier technology in sustainable manufacturing and enables end-of-life products to be restored to their new conditions. Although remanufacturing scheduling has been widely investigated, the relationship between remanufacturers and customers is rarely examined. Therefore, a new game-relationship-based remanufacturing scheduling model with sequence-dependent setup times is proposed herein. In the model, the relationship between the remanufacturer and customers is constructed as a non-cooperative game, and the interval due dates are set based on the uncertain product quality to achieve effective remanufacturing and improve customer satisfaction. Multiple remanufacturing lines differentiated based on the quality grade of products are integrated into the proposed model. In addition, sequence-dependent setup times are considered in the model, which depend on the similarity between two adjacent tasks processed on a reprocessing unit. An improved discrete particle swarm optimization algorithm is proposed to obtain Nash equilibrium solutions via an efficient global search structure and a local search strategy. The algorithm is embedded with the Nash equilibrium solution evaluation method and integrated with multiple genetic operators to update the particles. The performance of the proposed algorithm in solving the proposed model is verified via a comparison with three baseline algorithms for managing different problem instances.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"57 1","pages":"424 - 441"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90771195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-22DOI: 10.1177/1063293X221121819
Abdelhamid Bendjelloul, B. Mihoubi, M. Gaham, M. Moufid, B. Bouzouia
The rise of the fourth industrial revolution and the interest in autonomous production led to increased adoption of Cyber-Physical Production Systems (CPPS) in the industry. Due to the significant suitability of Multi-Agent Systems in building cyber-physical production systems compliant with the Reference Architectural Model Industry 4.0 (RAMI 4.0), more CPPS are being realized using Industrial Agents. Because of their complexity, guidelines for conducting virtual commissioning of agent-based CPPS are required. This paper proposes a novel framework for the virtual commissioning of agent-based CPPS. The framework contributions reside in incorporating both high-level and low-level control verification and validation (V&V) and employing two combined SIL and HIL approaches during the virtual commissioning of agent-based CPPS. The feasibility of the framework was demonstrated during the V&V of an agent-based CPPS on an industrial-scale laboratory robotized production cell. The framework had a significant impact on reducing the cost and efforts of the agent-based CPPS virtual commissioning.
{"title":"A framework for an effective virtual commissioning of agent-based cyber-physical production systems integrated into manufacturing facilities","authors":"Abdelhamid Bendjelloul, B. Mihoubi, M. Gaham, M. Moufid, B. Bouzouia","doi":"10.1177/1063293X221121819","DOIUrl":"https://doi.org/10.1177/1063293X221121819","url":null,"abstract":"The rise of the fourth industrial revolution and the interest in autonomous production led to increased adoption of Cyber-Physical Production Systems (CPPS) in the industry. Due to the significant suitability of Multi-Agent Systems in building cyber-physical production systems compliant with the Reference Architectural Model Industry 4.0 (RAMI 4.0), more CPPS are being realized using Industrial Agents. Because of their complexity, guidelines for conducting virtual commissioning of agent-based CPPS are required. This paper proposes a novel framework for the virtual commissioning of agent-based CPPS. The framework contributions reside in incorporating both high-level and low-level control verification and validation (V&V) and employing two combined SIL and HIL approaches during the virtual commissioning of agent-based CPPS. The feasibility of the framework was demonstrated during the V&V of an agent-based CPPS on an industrial-scale laboratory robotized production cell. The framework had a significant impact on reducing the cost and efforts of the agent-based CPPS virtual commissioning.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"14 1","pages":"399 - 410"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85153878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-18DOI: 10.1177/1063293X221114666
Jun Wang, Xiangqi Liu, Wenyu Zhang, Junliang Xu
With the increasingly serious problem of environmental pollution and resource scarcity, remanufacturing has become one of the popular research fields to solve these issues. However, the practical information of end-of-life products is different (e.g. type and degree of damage) because of their various operation conditions, which complicates the reprocessing routes. Therefore, a new remanufacturing system scheduling model is proposed in this study that considers not only the coordination of remanufacturing subsystems but also job-shop-type reprocessing shops related to the diversified reprocessing routes. A hybrid meta-heuristic algorithm combining differential evolution algorithm and biogeography-based optimization algorithm through a new representation scheme is presented to address the model efficiently. Furthermore, the basic algorithms are improved by integrating the self-adaptive parameters, efficient migration and mutation operators, local search strategy, and restart strategy. Simulation experiments are performed to demonstrate the effectiveness and practicality of the proposed method compared with four baseline algorithms.
{"title":"A new remanufacturing system scheduling model with diversified reprocessing routes using a hybrid meta-heuristic algorithm","authors":"Jun Wang, Xiangqi Liu, Wenyu Zhang, Junliang Xu","doi":"10.1177/1063293X221114666","DOIUrl":"https://doi.org/10.1177/1063293X221114666","url":null,"abstract":"With the increasingly serious problem of environmental pollution and resource scarcity, remanufacturing has become one of the popular research fields to solve these issues. However, the practical information of end-of-life products is different (e.g. type and degree of damage) because of their various operation conditions, which complicates the reprocessing routes. Therefore, a new remanufacturing system scheduling model is proposed in this study that considers not only the coordination of remanufacturing subsystems but also job-shop-type reprocessing shops related to the diversified reprocessing routes. A hybrid meta-heuristic algorithm combining differential evolution algorithm and biogeography-based optimization algorithm through a new representation scheme is presented to address the model efficiently. Furthermore, the basic algorithms are improved by integrating the self-adaptive parameters, efficient migration and mutation operators, local search strategy, and restart strategy. Simulation experiments are performed to demonstrate the effectiveness and practicality of the proposed method compared with four baseline algorithms.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"48 1","pages":"283 - 299"},"PeriodicalIF":0.0,"publicationDate":"2022-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78220677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Most enterprises focus on product portfolio management (PPM) and exclude market portfolio management, and individual markets are selected solely based on financial performance which may not be appropriate because other factors may dictate the outcome of the market selection. This study proposes a market portfolio model that considers market share, market growth, market competition, market risk, and market cost to maximize overall profit. A three-stage approach is proposed to identify potential product markets using an AI algorithm. A set of the most promising market is then determined based on the results of Stage 1 using a fuzzy multi-objective mathematical programming model by concurrently maximizing the total market share and market growth, and minimizing the market competition and market risk. A single-objective mathematical programming model is then used to determine a market portfolio to maximize the total profit using the results for Stage 2. The single-objective model is tested using two sets of threshold constraints. The balance of the market portfolio is discussed and the results are compared. The novelty of the article: (1) the first study involves a product market portfolio, (2) the decision of market selection is scientific (using AI instead of personal judgment), holistic (factors include market share, growth, competition, risk, cost, and profit) and optimized (using mathematical optimization), and (3) the market portfolio maximizes total profit. (4) the proposed method produces a portfolio with a higher profit than the TOPSIS method.
{"title":"Selecting and balancing market portfolio using artificial intelligence and fuzzy multiobjective decision-making model","authors":"Wen-Lung Shih, Chiu-Chi Wei, Hsien-Hong Lin, Pin-Hsiang Chang","doi":"10.1177/1063293X221115768","DOIUrl":"https://doi.org/10.1177/1063293X221115768","url":null,"abstract":"Most enterprises focus on product portfolio management (PPM) and exclude market portfolio management, and individual markets are selected solely based on financial performance which may not be appropriate because other factors may dictate the outcome of the market selection. This study proposes a market portfolio model that considers market share, market growth, market competition, market risk, and market cost to maximize overall profit. A three-stage approach is proposed to identify potential product markets using an AI algorithm. A set of the most promising market is then determined based on the results of Stage 1 using a fuzzy multi-objective mathematical programming model by concurrently maximizing the total market share and market growth, and minimizing the market competition and market risk. A single-objective mathematical programming model is then used to determine a market portfolio to maximize the total profit using the results for Stage 2. The single-objective model is tested using two sets of threshold constraints. The balance of the market portfolio is discussed and the results are compared. The novelty of the article: (1) the first study involves a product market portfolio, (2) the decision of market selection is scientific (using AI instead of personal judgment), holistic (factors include market share, growth, competition, risk, cost, and profit) and optimized (using mathematical optimization), and (3) the market portfolio maximizes total profit. (4) the proposed method produces a portfolio with a higher profit than the TOPSIS method.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"72 1","pages":"382 - 398"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77999776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-12DOI: 10.1177/1063293X221120084
Sadhana Sa, Sabena S, S. L, K. A
In the field of marketing, many surveys were conducted to analyze the customer satisfaction on products in their online purchases. But the real view of customers about the product is mirrored in the customer’s online reviews (COR) given by them, while they purchase the product online. This paper is the one for analyzing and distinguishing the real view about the customer satisfaction by reviewing their opinions for the product which they buy. As a part of opinion mining, the polarity of the specific word is extracted and classifies the review as positive or negative using Naïve Bayes classifier. And this creates a genuine view about the product from the customer point of view. The real opinion about the customer view on online shopping is going to be distinguished according to the intelligent rules generated based on the hypothesis. Intelligent rules help to classify the reviews by extracting the real opinion of the customer based on the feature they specified for the product which is purchased by the consumer. This kind of feature-based review classification supports the purchase of new users when they approach online shopping. This work also projects the customer view about which feature they really need and also feel good, from their review representation.
{"title":"Customer’s opinion mining from online reviews using intelligent rules with machine learning techniques","authors":"Sadhana Sa, Sabena S, S. L, K. A","doi":"10.1177/1063293X221120084","DOIUrl":"https://doi.org/10.1177/1063293X221120084","url":null,"abstract":"In the field of marketing, many surveys were conducted to analyze the customer satisfaction on products in their online purchases. But the real view of customers about the product is mirrored in the customer’s online reviews (COR) given by them, while they purchase the product online. This paper is the one for analyzing and distinguishing the real view about the customer satisfaction by reviewing their opinions for the product which they buy. As a part of opinion mining, the polarity of the specific word is extracted and classifies the review as positive or negative using Naïve Bayes classifier. And this creates a genuine view about the product from the customer point of view. The real opinion about the customer view on online shopping is going to be distinguished according to the intelligent rules generated based on the hypothesis. Intelligent rules help to classify the reviews by extracting the real opinion of the customer based on the feature they specified for the product which is purchased by the consumer. This kind of feature-based review classification supports the purchase of new users when they approach online shopping. This work also projects the customer view about which feature they really need and also feel good, from their review representation.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"26 1","pages":"344 - 352"},"PeriodicalIF":0.0,"publicationDate":"2022-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77615002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-09DOI: 10.1177/1063293X221114937
Vinothkumar C, E. C
The paper work focuses on soft computing and Conventional controller tuning approach to design of PI controller, for a nonlinear hopper tank liquid level control system process Industries. The automation industries provide conventional techniques where it is impossible to maintain its settling time which motivates to do the research in this field. The system processes the combination of a conical and cylindrical tank for providing Multi-region based mathematical modelling to obtain the first order with delay time (FOPDT) process transfer function model. The Ziegler Nichols, Cohen-coon, Tyreus Luben, CHR (Chien, Hrones, and Reswick), IMC (Internal Model Control), Direct Synthesis, FOPI(Fractional Order PI) Conventional tuning formulae and Cuckoo Search Optimization (CSO) algorithm are used to optimize the servo regulatory responses of PI controller. The integral and proportional gain of the PI controller is said to produce the fastest settling time and reduces the error using performance indices and achieves Liquid Level control in hopper tank. Comparison is made for the various conventional controller tuning methods with Cuckoo Search Optimization tuning responses and identified to CSO-PI method offers enhanced Optimized Performance of settling time which was about 105.58 s which is relatively less while comparing to Conventional PI controller tuning methods for a different region based system.
{"title":"Cuckoo Search Optimization based PI Controller Tuning for Hopper Tank System","authors":"Vinothkumar C, E. C","doi":"10.1177/1063293X221114937","DOIUrl":"https://doi.org/10.1177/1063293X221114937","url":null,"abstract":"The paper work focuses on soft computing and Conventional controller tuning approach to design of PI controller, for a nonlinear hopper tank liquid level control system process Industries. The automation industries provide conventional techniques where it is impossible to maintain its settling time which motivates to do the research in this field. The system processes the combination of a conical and cylindrical tank for providing Multi-region based mathematical modelling to obtain the first order with delay time (FOPDT) process transfer function model. The Ziegler Nichols, Cohen-coon, Tyreus Luben, CHR (Chien, Hrones, and Reswick), IMC (Internal Model Control), Direct Synthesis, FOPI(Fractional Order PI) Conventional tuning formulae and Cuckoo Search Optimization (CSO) algorithm are used to optimize the servo regulatory responses of PI controller. The integral and proportional gain of the PI controller is said to produce the fastest settling time and reduces the error using performance indices and achieves Liquid Level control in hopper tank. Comparison is made for the various conventional controller tuning methods with Cuckoo Search Optimization tuning responses and identified to CSO-PI method offers enhanced Optimized Performance of settling time which was about 105.58 s which is relatively less while comparing to Conventional PI controller tuning methods for a different region based system.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"38 1","pages":"300 - 308"},"PeriodicalIF":0.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78822308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-08DOI: 10.1177/1063293X221120648
K. Vijayakumar
The proposed special issue focuses on collecting the research articles on recent advancements in the research domains, like intelligent computing, communication and IIoT applications. The selected articles in this issue are closely related to the theme of the special issue. It provides a cutting edge research works from a set of carefully selected researchers. This editorial presents the outline of the research articles associated with the special issue.
{"title":"Special issue on intelligent computing and communication in industrial internet of things","authors":"K. Vijayakumar","doi":"10.1177/1063293X221120648","DOIUrl":"https://doi.org/10.1177/1063293X221120648","url":null,"abstract":"The proposed special issue focuses on collecting the research articles on recent advancements in the research domains, like intelligent computing, communication and IIoT applications. The selected articles in this issue are closely related to the theme of the special issue. It provides a cutting edge research works from a set of carefully selected researchers. This editorial presents the outline of the research articles associated with the special issue.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"33 1","pages":"227 - 228"},"PeriodicalIF":0.0,"publicationDate":"2022-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87429140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-06DOI: 10.1177/1063293X221117865
Ting Wang, Jingchun Feng
Concurrent execution of design and construction tasks is an important way to realize the integration of them in design-build (DB) mode, but it may bring about period risk due to multiple rework and frequent information transfer in local scope. To solve this problem, this study constructs a concurrent execution strategy model from the perspective of quantitative analysis with the decision goal of minimizing the total execution duration. The results show that: first, when the probability of information change between design and construction tasks decreases gradually, the optimal overlap degree increases and the optimal parallelism decreases. Second, learning effect can effectively shorten the minimum duration corresponding to the optimal overlap degree under any degree of parallelism. Thirdly, with the decrease of the probability of information change between design and construction tasks and the strengthening of learning effect, the shortening rate of the actual execution duration corresponding to the optimal parallelism will be gradually greater than the increasing rate of the actual execution duration. The findings of the study provide suggestions for exploring the mechanism of concurrent execution in DB mode, and also provide countermeasures for better realization of integration of design and construction in DB mode.
{"title":"Modeling and optimization of concurrent execution process of coupled design-construction tasks under design-build mode","authors":"Ting Wang, Jingchun Feng","doi":"10.1177/1063293X221117865","DOIUrl":"https://doi.org/10.1177/1063293X221117865","url":null,"abstract":"Concurrent execution of design and construction tasks is an important way to realize the integration of them in design-build (DB) mode, but it may bring about period risk due to multiple rework and frequent information transfer in local scope. To solve this problem, this study constructs a concurrent execution strategy model from the perspective of quantitative analysis with the decision goal of minimizing the total execution duration. The results show that: first, when the probability of information change between design and construction tasks decreases gradually, the optimal overlap degree increases and the optimal parallelism decreases. Second, learning effect can effectively shorten the minimum duration corresponding to the optimal overlap degree under any degree of parallelism. Thirdly, with the decrease of the probability of information change between design and construction tasks and the strengthening of learning effect, the shortening rate of the actual execution duration corresponding to the optimal parallelism will be gradually greater than the increasing rate of the actual execution duration. The findings of the study provide suggestions for exploring the mechanism of concurrent execution in DB mode, and also provide countermeasures for better realization of integration of design and construction in DB mode.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"92 1","pages":"353 - 366"},"PeriodicalIF":0.0,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83811990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：