The Italian textile machinery sector,renowned for its technological excellence and innovative capacity,continues to navigate a complex global market with a strategic emphasis on digitalization,sustainability,and stron...The Italian textile machinery sector,renowned for its technological excellence and innovative capacity,continues to navigate a complex global market with a strategic emphasis on digitalization,sustainability,and strong customer partnerships.Marco Salvade’,President of ACIMIT,provided insights into the industry’s performance,key trends,and future directions.In the first quarter of 2025,Italian textile machinery exports saw a 6%decrease compared to the same period in 2024,totaling€363 million.This dip reflects ongoing geopolitical tensions and a cautious approach among global clients toward new investments.Despite these challenges,Italian manufacturers maintain a strong reputation for technological leadership and resilience.展开更多
Supplier selection in a mass customization environment is a systematic engineering,and Quality Function Deployment(QFD)based on customer demand is a systematic product development method.This paper studies the adaptab...Supplier selection in a mass customization environment is a systematic engineering,and Quality Function Deployment(QFD)based on customer demand is a systematic product development method.This paper studies the adaptability of the QFD method and supplier selection process in a mass customization environment and puts forward a supplier selection framework based on the QFD idea.Furthermore,both the objective environment of demand factor analysis and the thinking of the customer representatives participating in the analysis have great uncertainty and fuzziness.Therefore,a demand factor analysis method for supplier selection in the mass customization environment based on language phrases of different granularity is proposed.The proposed method allows the customer representatives participating in the selection to use their preferred language phrase set to represent the importance of demand factors.Finally,the effectiveness and feasibility of the proposed method are verified by an example of a vehicle manufacturer.展开更多
Cyber-Physical Networks(CPN)are comprehensive systems that integrate information and physical domains,and are widely used in various fields such as online social networking,smart grids,and the Internet of Vehicles(IoV...Cyber-Physical Networks(CPN)are comprehensive systems that integrate information and physical domains,and are widely used in various fields such as online social networking,smart grids,and the Internet of Vehicles(IoV).With the increasing popularity of digital photography and Internet technology,more and more users are sharing images on CPN.However,many images are shared without any privacy processing,exposing hidden privacy risks and making sensitive content easily accessible to Artificial Intelligence(AI)algorithms.Existing image sharing methods lack fine-grained image sharing policies and cannot protect user privacy.To address this issue,we propose a social relationship-driven privacy customization protection model for publishers and co-photographers.We construct a heterogeneous social information network centered on social relationships,introduce a user intimacy evaluation method with time decay,and evaluate privacy levels considering user interest similarity.To protect user privacy while maintaining image appreciation,we design a lightweight face-swapping algorithm based on Generative Adversarial Network(GAN)to swap faces that need to be protected.Our proposed method minimizes the loss of image utility while satisfying privacy requirements,as shown by extensive theoretical and simulation analyses.展开更多
The rapid advancement of Industry 4.0 has revolutionized manufacturing,shifting production from centralized control to decentralized,intelligent systems.Smart factories are now expected to achieve high adaptability an...The rapid advancement of Industry 4.0 has revolutionized manufacturing,shifting production from centralized control to decentralized,intelligent systems.Smart factories are now expected to achieve high adaptability and resource efficiency,particularly in mass customization scenarios where production schedules must accommodate dynamic and personalized demands.To address the challenges of dynamic task allocation,uncertainty,and realtime decision-making,this paper proposes Pathfinder,a deep reinforcement learning-based scheduling framework.Pathfinder models scheduling data through three key matrices:execution time(the time required for a job to complete),completion time(the actual time at which a job is finished),and efficiency(the performance of executing a single job).By leveraging neural networks,Pathfinder extracts essential features from these matrices,enabling intelligent decision-making in dynamic production environments.Unlike traditional approaches with fixed scheduling rules,Pathfinder dynamically selects from ten diverse scheduling rules,optimizing decisions based on real-time environmental conditions.To further enhance scheduling efficiency,a specialized reward function is designed to support dynamic task allocation and real-time adjustments.This function helps Pathfinder continuously refine its scheduling strategy,improving machine utilization and minimizing job completion times.Through reinforcement learning,Pathfinder adapts to evolving production demands,ensuring robust performance in real-world applications.Experimental results demonstrate that Pathfinder outperforms traditional scheduling approaches,offering improved coordination and efficiency in smart factories.By integrating deep reinforcement learning,adaptable scheduling strategies,and an innovative reward function,Pathfinder provides an effective solution to the growing challenges of multi-robot job scheduling in mass customization environments.展开更多
Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying ...Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.展开更多
In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and ta...In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.展开更多
The increasing complexity and size of configuration knowledge bases requres the provisionof advanced methods supporting the development of the actual configuration process and design reuse.A new framework to find a fe...The increasing complexity and size of configuration knowledge bases requres the provisionof advanced methods supporting the development of the actual configuration process and design reuse.A new framework to find a feasible and practical product configuration method is presented in masscustomization. The basic idea of the appoach is to integrate case-based reasoning (CBR) with a con-straint satisfaction problem(CSP). The similarity measure between a crisp and range is also given,which is common in case retrieves. Based on the configuration model, a product platform and customerneeds, case adaptation is carried out with the repair-based algorithm. Lastly, the methodology in theelevator configuration design domain is tested.展开更多
Product customization has been recognized as an effective means to implement mass cus-tomization （MC）. A new theory and method for MC-oriented evolutionary design of configuration product is presented based on the s...Product customization has been recognized as an effective means to implement mass cus-tomization （MC）. A new theory and method for MC-oriented evolutionary design of configuration product is presented based on the study of developing law of evolutionary design in integrated envi-ronment, which focuses on the innovation and reuse properties of configuration product. The key technologies for general requirement modeling in quick response to customer requirement, multi-level stepwise configuration optimization driven by customer requirement and evolutionary deduction of product variable structure based on configuration association are thoroughly investigated. The suc-cessful application of the presented method in the development of real-life products demonstrates its utility, flexibility and robusticity.展开更多
The paper presents a design method that ensures the ingenuity of the product form as well as the whole and exact expression of user’s needs. The key idea is to establish an automatic design system which can transform...The paper presents a design method that ensures the ingenuity of the product form as well as the whole and exact expression of user’s needs. The key idea is to establish an automatic design system which can transform the user’s language needs into the product features in real-time. A rifle was taken as a research instance and soldiers were chosen as evaluation customers. The theory of fuzzy set and semantic difference are adopted to evaluate the relationship between user’s needs and product features as well as their alternatives. FAHP (fuzzy analytic hierarchy process) is utilized to judge the user’s satisfactory forms. This method can also be applied to other product form designs.展开更多
Social manufacturing(SM), a novel distributed,collaborative and intelligent manufacturing mode, is proposed and developed for high-end apparel customization. The main components of SM cloud are designed, and its resea...Social manufacturing(SM), a novel distributed,collaborative and intelligent manufacturing mode, is proposed and developed for high-end apparel customization. The main components of SM cloud are designed, and its research topics are summarized. Then, SM's key technologies are studied. 3D technologies for apparel customization, like 3D modeling, 3D fitting mirror and 3D customization, are developed to improve the customization precision and user experience. Information based collaborative management is realized to share, communicate,and handle the information efficiently among all groups and individuals of SM cloud. Suppliers' evaluation mechanism is designed to support the optimal decisions making. Next, SM cloud is constructed in five layers for high-end apparel customization.By using SM cloud based crowd-sourcing, social resources can be allocated rationally and utilized efficiently, consumer can customize the product in any processes like innovation, design,making, marketing and service, and traditional apparel enterprise can be upgraded into SM mode for keeping it competitive in the future customization markets.展开更多
A group of graphical models and mathematical models a re used to describe the methods of mass customization (MC). The relationships am ong the models and methods are shown in Fig.1. Fig.1 Relationships among optimizat...A group of graphical models and mathematical models a re used to describe the methods of mass customization (MC). The relationships am ong the models and methods are shown in Fig.1. Fig.1 Relationships among optimization methods for MCThe methods for MC relate to both of product and process, also customized quanti ty and deepness. The methods for MC are integrated by the work in the paper, whi ch can help to understand and use MC better. The optimization and standardization of product is the key for MC. Increasing op timization breadth in product family can help to decrease the customization quan tity in every section of production process. Increasing optimization deepness in products family can help to move the CODCP backward in production process. At the same time, the optimization and standardization of product is the key to reduce cost of customized product. The optimization of the integration of pr oduct and process is the key to reduce lead time of customized product.展开更多
The airlines need to select the optional equipment according to their individual development demands and the manufacture′s standard specification manual when purchasing a new airplane.For this customization process,t...The airlines need to select the optional equipment according to their individual development demands and the manufacture′s standard specification manual when purchasing a new airplane.For this customization process,the selection theory is mainly based on qualitative analysis and quantitative analysis.The grey incidence analysis(GIA)is used for modeling,which evaluates the correlations between optional equipment and airlines′individual demands.Meanwhile,the customization demands are quantitatively processed as different weights in evaluation index system with analytical hierarchy process.Then,the value of grey incidence degree is obtained which shows whether the optional equipment is on the purchasing list or not.Finally,two airlines′customization demands are applied in the example of aircraft cabin′s seats,so two different purchasing priorities and equipment installation lists can be obtained.The results and comparisons verify the reasonable of modeling,which provides an objective scheme of aircraft equipment selection.展开更多
Objectives: This article describes how to make a customized tracheostomy tube immediately in the operating room setting. This is particularly critical when a commercial customized tracheostomy tube cannot be readily o...Objectives: This article describes how to make a customized tracheostomy tube immediately in the operating room setting. This is particularly critical when a commercial customized tracheostomy tube cannot be readily obtained. Study Design: Case presentation. Methods/Results: A 73-year-old female was seen in our clinic for management of a recurrent invasive paraganglioma of the thyroid. She underwent a total laryngopharyngectomy, cervical esophagectomy, and anterolateral thigh free flap reconstruction followed by post-operative radiation. In follow-up, the patient presented with dyspnea related to two areas of stenosis, one at the level of her stoma and one at the distal trachea. The patient was therefore taken to the operating room urgently for dilation and placement of a tracheostomy tube. Available tracheostomy tubes were tried and ill fitting as each tube narrowed the patient’s stoma or abutted her distal granulation tissue. To custom create a tracheostomy tube, we used a standard rib shearer to shorten a #6 uncuffed tracheostomy tube by 2 cm. The edges were further smoothed and beveled using sand paper and a diamond burr drill. The finished product was a wide diameter tube with a custom length suited to our patient. Conclusions: Although a simple solution, the use of a rib shearer provides a quick and feasible solution to creating custom length tracheostomy tubes in situations where custom length tubes are needed yet unavailable.展开更多
New requirements have been put forward by the age of "Internet+" to improve the abilities of reform,transformation and innovation for traditional carpet industry in combining the technology of the fully digi...New requirements have been put forward by the age of "Internet+" to improve the abilities of reform,transformation and innovation for traditional carpet industry in combining the technology of the fully digital fabric tufting and the system of networked intelligent customization that forms C2B mode of personalized customization of the digital carpet to promote the carpet industry to develop towards individuation,intelligence and high efficiency. Exploring the market background of C2B mode of intelligent customization of the digital carpet and developing the technology of the fully digital fabric tufting makes it possible to achieve personalized customization of the digital carpet. The industrial internet which is integrated by a lot of robots of the fully digital fabric tufting will change completely traditional carpet industry.展开更多
Customer requirements analysis is the key step for product variety design of mass customiza-tion(MC). Quality function deployment (QFD) is a widely used management technique for understanding the voice of the customer...Customer requirements analysis is the key step for product variety design of mass customiza-tion(MC). Quality function deployment (QFD) is a widely used management technique for understanding the voice of the customer (VOC), however, QFD depends heavily on human subject judgment during extracting customer requirements and determination of the importance weights of customer requirements. QFD pro-cess and related problems are so complicated that it is not easily used. In this paper, based on a general data structure of product family, generic bill of material (GBOM), association rules analysis was introduced to construct the classification mechanism between customer requirements and product architecture. The new method can map customer requirements to the items of product family architecture respectively, accomplish the mapping process from customer domain to physical domain directly, and decrease mutual process between customer and designer, improve the product design quality, and thus furthest satisfy customer needs. Finally, an example of customer requirements mapping of the elevator cabin was used to illustrate the proposed method.展开更多
On the basis of researching on requirement product configuration in mass customization, the concept of product family requirement class （PFRC） and requirement-matching template are put forward. A case-based requirem...On the basis of researching on requirement product configuration in mass customization, the concept of product family requirement class （PFRC） and requirement-matching template are put forward. A case-based requirement product configuration （CB-RPC） model and corresponding requirement product model are established. The result of requirement product configuration is obtained by using the method of two-level similar matching. In addition, the effect of the method on requirement responding is analyzed. Finally, the model and the method given are applied in elevator industry, and have improved the enterorise＇s ability of rapid responding to customer＇s reouirements.展开更多
The measurements of female aged from 18 to 50 in the East China are taken by TC2 3D-body scanner. The first five factors are obtained by factor analysis of SPSS from 25 items of the upper body which influence the body...The measurements of female aged from 18 to 50 in the East China are taken by TC2 3D-body scanner. The first five factors are obtained by factor analysis of SPSS from 25 items of the upper body which influence the body shape, that is, circumference factor, height factor, side shape factor, frontal shape factor, and shoulder slope factor. Then characteristic indices of upper body are chosen by analyzing body scan data. This study will be useful for developing pattern more fitting and faster and helpful for realizing apparel mass customization.展开更多
This paper breaks through the old study pattern,emphasizing the important of economic analysis and put forward the analytic method.The paper compares mass customization to just-in-time,analyses the two facets which in...This paper breaks through the old study pattern,emphasizing the important of economic analysis and put forward the analytic method.The paper compares mass customization to just-in-time,analyses the two facets which include production and distribution.The production facet is influence of the indirect cost,scale economy,experiences economy and dynamic alliance.The reduction of indirect cost is the innovation,which has special angle comparatively traditional economic analysis.There is gaming between satisfying customer special demand and deciding price.Mass customization emphasizes that customer must achieve to loyalty not only content without increasing extra service charge-faith in company and product.The paper sets forth the economics of scale e- conomy and dynamic alliance to embody the extensive economy.In addition it is another innovation that this paper analyses the de- fects of mass customization to evaluate the economic risk.Through comparing the traditional production mode,demonstrating the implement feasibility in company.That is mass customization has less economic risk whether or not.So the analysis proposes the evi- dences of the way of enterprise production.展开更多
Mass customization relates to the ability of providing individually designed products or services to customer with high process flexibility or integration.Literatures on mass customization have been focused on mechani...Mass customization relates to the ability of providing individually designed products or services to customer with high process flexibility or integration.Literatures on mass customization have been focused on mechanism of MC,but little on cus- tomer order decoupling point selection.The aim of this paper is to present a model for customer order decoupling point selection of domain knowledge interactions between enterprises and customers in mass customization.Based on the analysis of other researchers’ achievements combining the demand problems of customer and enterprise,a model of group decision for customer order decoupling point selection is constructed based on quality function deployment and multi-agent system.Considering relatively the decision mak- ers of independent functional departments as independent decision agents,a decision agent set is added as the third dimensionality to house of quality,the cubic quality function deployment is formed.The decision-making can be consisted of two procedures:the first one is to build each plane house of quality in various functional departments to express each opinions;the other is to evaluate and gather the foregoing sub-decisions by a new plane quality function deployment.Thus,department decision-making can well use its domain knowledge by ontology,and total decision-making can keep simple by avoiding too many customer requirements.展开更多
The successful implementation of mass customization lies on reengineeringtechnology and management methods to organize the production. Especially in assembly phase, variousproduct configurations, due-time penalties an...The successful implementation of mass customization lies on reengineeringtechnology and management methods to organize the production. Especially in assembly phase, variousproduct configurations, due-time penalties and order-driven strategy challenge the traditionaloperation and management of assembly lines. The business features and the operation pattern ofassembly line based on mass customization are analyzed. And the research emphatically studiesvarious technologic factors to improve customer satisfaction and their corresponding implementmethods in operating assembly line. In addition, the models are proposed for operating assembly lineunder dynamic process environment in mass customization. A genetic approach is developed to providethe optimal solution to the models. The effectiveness of the proposed approach is evaluated with anindustrial application.展开更多
文摘The Italian textile machinery sector,renowned for its technological excellence and innovative capacity,continues to navigate a complex global market with a strategic emphasis on digitalization,sustainability,and strong customer partnerships.Marco Salvade’,President of ACIMIT,provided insights into the industry’s performance,key trends,and future directions.In the first quarter of 2025,Italian textile machinery exports saw a 6%decrease compared to the same period in 2024,totaling€363 million.This dip reflects ongoing geopolitical tensions and a cautious approach among global clients toward new investments.Despite these challenges,Italian manufacturers maintain a strong reputation for technological leadership and resilience.
文摘Supplier selection in a mass customization environment is a systematic engineering,and Quality Function Deployment(QFD)based on customer demand is a systematic product development method.This paper studies the adaptability of the QFD method and supplier selection process in a mass customization environment and puts forward a supplier selection framework based on the QFD idea.Furthermore,both the objective environment of demand factor analysis and the thinking of the customer representatives participating in the analysis have great uncertainty and fuzziness.Therefore,a demand factor analysis method for supplier selection in the mass customization environment based on language phrases of different granularity is proposed.The proposed method allows the customer representatives participating in the selection to use their preferred language phrase set to represent the importance of demand factors.Finally,the effectiveness and feasibility of the proposed method are verified by an example of a vehicle manufacturer.
基金supported in part by National Natural Science Foundation of China(62271096,U20A20157)Natural Science Foundation of Chongqing,China(cstc2020jcyj-zdxmX0024,CSTB2022NSCQMSX0600)+5 种基金University Innovation Research Group of Chongqing(CXQT20017)Program for Innovation Team Building at Institutions of Higher Education in Chongqing(CXTDX201601020)Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN202000626)Youth Innovation Group Support Program of ICE Discipline of CQUPT(SCIE-QN-2022-04)the Science and Technology Research Program of Chongqing Municipal Education Commission under Grant KJQN202000626Chongqing Municipal Technology Innovation and Application Development Special Key Project(cstc2020jscx-dxwtBX0053)。
文摘Cyber-Physical Networks(CPN)are comprehensive systems that integrate information and physical domains,and are widely used in various fields such as online social networking,smart grids,and the Internet of Vehicles(IoV).With the increasing popularity of digital photography and Internet technology,more and more users are sharing images on CPN.However,many images are shared without any privacy processing,exposing hidden privacy risks and making sensitive content easily accessible to Artificial Intelligence(AI)algorithms.Existing image sharing methods lack fine-grained image sharing policies and cannot protect user privacy.To address this issue,we propose a social relationship-driven privacy customization protection model for publishers and co-photographers.We construct a heterogeneous social information network centered on social relationships,introduce a user intimacy evaluation method with time decay,and evaluate privacy levels considering user interest similarity.To protect user privacy while maintaining image appreciation,we design a lightweight face-swapping algorithm based on Generative Adversarial Network(GAN)to swap faces that need to be protected.Our proposed method minimizes the loss of image utility while satisfying privacy requirements,as shown by extensive theoretical and simulation analyses.
基金supported by National Natural Science Foundation of China under Grant No.62372110Fujian Provincial Natural Science of Foundation under Grants 2023J02008,2024H0009.
文摘The rapid advancement of Industry 4.0 has revolutionized manufacturing,shifting production from centralized control to decentralized,intelligent systems.Smart factories are now expected to achieve high adaptability and resource efficiency,particularly in mass customization scenarios where production schedules must accommodate dynamic and personalized demands.To address the challenges of dynamic task allocation,uncertainty,and realtime decision-making,this paper proposes Pathfinder,a deep reinforcement learning-based scheduling framework.Pathfinder models scheduling data through three key matrices:execution time(the time required for a job to complete),completion time(the actual time at which a job is finished),and efficiency(the performance of executing a single job).By leveraging neural networks,Pathfinder extracts essential features from these matrices,enabling intelligent decision-making in dynamic production environments.Unlike traditional approaches with fixed scheduling rules,Pathfinder dynamically selects from ten diverse scheduling rules,optimizing decisions based on real-time environmental conditions.To further enhance scheduling efficiency,a specialized reward function is designed to support dynamic task allocation and real-time adjustments.This function helps Pathfinder continuously refine its scheduling strategy,improving machine utilization and minimizing job completion times.Through reinforcement learning,Pathfinder adapts to evolving production demands,ensuring robust performance in real-world applications.Experimental results demonstrate that Pathfinder outperforms traditional scheduling approaches,offering improved coordination and efficiency in smart factories.By integrating deep reinforcement learning,adaptable scheduling strategies,and an innovative reward function,Pathfinder provides an effective solution to the growing challenges of multi-robot job scheduling in mass customization environments.
文摘Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.
文摘In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.
基金This project is supported by National Natural Science Foundation of China(No.50275133) and China Hi-tech Program CIMS Topic (No.2003-China(No.50275133) and China Hi-tech Program CIMS Topic (No.2003-AA411320). Received July 22, 2003
文摘The increasing complexity and size of configuration knowledge bases requres the provisionof advanced methods supporting the development of the actual configuration process and design reuse.A new framework to find a feasible and practical product configuration method is presented in masscustomization. The basic idea of the appoach is to integrate case-based reasoning (CBR) with a con-straint satisfaction problem(CSP). The similarity measure between a crisp and range is also given,which is common in case retrieves. Based on the configuration model, a product platform and customerneeds, case adaptation is carried out with the repair-based algorithm. Lastly, the methodology in theelevator configuration design domain is tested.
基金This project is supported by National Natural Science Foundation of China (No. 50505044, No. 60573175)Postdoctoral Foundation of China (No. 2005037816).
文摘Product customization has been recognized as an effective means to implement mass cus-tomization （MC）. A new theory and method for MC-oriented evolutionary design of configuration product is presented based on the study of developing law of evolutionary design in integrated envi-ronment, which focuses on the innovation and reuse properties of configuration product. The key technologies for general requirement modeling in quick response to customer requirement, multi-level stepwise configuration optimization driven by customer requirement and evolutionary deduction of product variable structure based on configuration association are thoroughly investigated. The suc-cessful application of the presented method in the development of real-life products demonstrates its utility, flexibility and robusticity.
文摘The paper presents a design method that ensures the ingenuity of the product form as well as the whole and exact expression of user’s needs. The key idea is to establish an automatic design system which can transform the user’s language needs into the product features in real-time. A rifle was taken as a research instance and soldiers were chosen as evaluation customers. The theory of fuzzy set and semantic difference are adopted to evaluate the relationship between user’s needs and product features as well as their alternatives. FAHP (fuzzy analytic hierarchy process) is utilized to judge the user’s satisfactory forms. This method can also be applied to other product form designs.
基金supported in part by the National Natural Science Foundation of China(71232006,61533019,61233001,61304201,61773381,61773382,71472174,71702182)Finnish TEKESs project“SoMa 2020:Social Manufacturing”(2015-2017,211560)+1 种基金Chinese Guangdong’s S&T Project(2015B010103001,2016B090910001,2017B090912001)Dongguan’s Innovation Talents Project(Gang Xiong)
文摘Social manufacturing(SM), a novel distributed,collaborative and intelligent manufacturing mode, is proposed and developed for high-end apparel customization. The main components of SM cloud are designed, and its research topics are summarized. Then, SM's key technologies are studied. 3D technologies for apparel customization, like 3D modeling, 3D fitting mirror and 3D customization, are developed to improve the customization precision and user experience. Information based collaborative management is realized to share, communicate,and handle the information efficiently among all groups and individuals of SM cloud. Suppliers' evaluation mechanism is designed to support the optimal decisions making. Next, SM cloud is constructed in five layers for high-end apparel customization.By using SM cloud based crowd-sourcing, social resources can be allocated rationally and utilized efficiently, consumer can customize the product in any processes like innovation, design,making, marketing and service, and traditional apparel enterprise can be upgraded into SM mode for keeping it competitive in the future customization markets.
文摘A group of graphical models and mathematical models a re used to describe the methods of mass customization (MC). The relationships am ong the models and methods are shown in Fig.1. Fig.1 Relationships among optimization methods for MCThe methods for MC relate to both of product and process, also customized quanti ty and deepness. The methods for MC are integrated by the work in the paper, whi ch can help to understand and use MC better. The optimization and standardization of product is the key for MC. Increasing op timization breadth in product family can help to decrease the customization quan tity in every section of production process. Increasing optimization deepness in products family can help to move the CODCP backward in production process. At the same time, the optimization and standardization of product is the key to reduce cost of customized product. The optimization of the integration of pr oduct and process is the key to reduce lead time of customized product.
文摘The airlines need to select the optional equipment according to their individual development demands and the manufacture′s standard specification manual when purchasing a new airplane.For this customization process,the selection theory is mainly based on qualitative analysis and quantitative analysis.The grey incidence analysis(GIA)is used for modeling,which evaluates the correlations between optional equipment and airlines′individual demands.Meanwhile,the customization demands are quantitatively processed as different weights in evaluation index system with analytical hierarchy process.Then,the value of grey incidence degree is obtained which shows whether the optional equipment is on the purchasing list or not.Finally,two airlines′customization demands are applied in the example of aircraft cabin′s seats,so two different purchasing priorities and equipment installation lists can be obtained.The results and comparisons verify the reasonable of modeling,which provides an objective scheme of aircraft equipment selection.
文摘Objectives: This article describes how to make a customized tracheostomy tube immediately in the operating room setting. This is particularly critical when a commercial customized tracheostomy tube cannot be readily obtained. Study Design: Case presentation. Methods/Results: A 73-year-old female was seen in our clinic for management of a recurrent invasive paraganglioma of the thyroid. She underwent a total laryngopharyngectomy, cervical esophagectomy, and anterolateral thigh free flap reconstruction followed by post-operative radiation. In follow-up, the patient presented with dyspnea related to two areas of stenosis, one at the level of her stoma and one at the distal trachea. The patient was therefore taken to the operating room urgently for dilation and placement of a tracheostomy tube. Available tracheostomy tubes were tried and ill fitting as each tube narrowed the patient’s stoma or abutted her distal granulation tissue. To custom create a tracheostomy tube, we used a standard rib shearer to shorten a #6 uncuffed tracheostomy tube by 2 cm. The edges were further smoothed and beveled using sand paper and a diamond burr drill. The finished product was a wide diameter tube with a custom length suited to our patient. Conclusions: Although a simple solution, the use of a rib shearer provides a quick and feasible solution to creating custom length tracheostomy tubes in situations where custom length tubes are needed yet unavailable.
文摘New requirements have been put forward by the age of "Internet+" to improve the abilities of reform,transformation and innovation for traditional carpet industry in combining the technology of the fully digital fabric tufting and the system of networked intelligent customization that forms C2B mode of personalized customization of the digital carpet to promote the carpet industry to develop towards individuation,intelligence and high efficiency. Exploring the market background of C2B mode of intelligent customization of the digital carpet and developing the technology of the fully digital fabric tufting makes it possible to achieve personalized customization of the digital carpet. The industrial internet which is integrated by a lot of robots of the fully digital fabric tufting will change completely traditional carpet industry.
基金the National Natural Science Founda-tion of China (No. 70471022)the NSFC / Hong KongResearch Grant Council (No. 70418013)
文摘Customer requirements analysis is the key step for product variety design of mass customiza-tion(MC). Quality function deployment (QFD) is a widely used management technique for understanding the voice of the customer (VOC), however, QFD depends heavily on human subject judgment during extracting customer requirements and determination of the importance weights of customer requirements. QFD pro-cess and related problems are so complicated that it is not easily used. In this paper, based on a general data structure of product family, generic bill of material (GBOM), association rules analysis was introduced to construct the classification mechanism between customer requirements and product architecture. The new method can map customer requirements to the items of product family architecture respectively, accomplish the mapping process from customer domain to physical domain directly, and decrease mutual process between customer and designer, improve the product design quality, and thus furthest satisfy customer needs. Finally, an example of customer requirements mapping of the elevator cabin was used to illustrate the proposed method.
基金This project is supported by National Basic Research Program of China (973 Program, No.2004CB719402)National Natural Science Foundation of China(No.50475072, No.50275133)National Hi-tech Research and Development Program of China(863 Program, No.2003-AA411320).
文摘On the basis of researching on requirement product configuration in mass customization, the concept of product family requirement class （PFRC） and requirement-matching template are put forward. A case-based requirement product configuration （CB-RPC） model and corresponding requirement product model are established. The result of requirement product configuration is obtained by using the method of two-level similar matching. In addition, the effect of the method on requirement responding is analyzed. Finally, the model and the method given are applied in elevator industry, and have improved the enterorise＇s ability of rapid responding to customer＇s reouirements.
文摘The measurements of female aged from 18 to 50 in the East China are taken by TC2 3D-body scanner. The first five factors are obtained by factor analysis of SPSS from 25 items of the upper body which influence the body shape, that is, circumference factor, height factor, side shape factor, frontal shape factor, and shoulder slope factor. Then characteristic indices of upper body are chosen by analyzing body scan data. This study will be useful for developing pattern more fitting and faster and helpful for realizing apparel mass customization.
文摘This paper breaks through the old study pattern,emphasizing the important of economic analysis and put forward the analytic method.The paper compares mass customization to just-in-time,analyses the two facets which include production and distribution.The production facet is influence of the indirect cost,scale economy,experiences economy and dynamic alliance.The reduction of indirect cost is the innovation,which has special angle comparatively traditional economic analysis.There is gaming between satisfying customer special demand and deciding price.Mass customization emphasizes that customer must achieve to loyalty not only content without increasing extra service charge-faith in company and product.The paper sets forth the economics of scale e- conomy and dynamic alliance to embody the extensive economy.In addition it is another innovation that this paper analyses the de- fects of mass customization to evaluate the economic risk.Through comparing the traditional production mode,demonstrating the implement feasibility in company.That is mass customization has less economic risk whether or not.So the analysis proposes the evi- dences of the way of enterprise production.
基金Supported by the National Natural Science Foundation,China(No.70571019)the National High-Tech.R&D Program for CIMS,China(No.2002AA413110)the National Defense Basic Science and Research Foundation,China(No.A2320060097)
文摘Mass customization relates to the ability of providing individually designed products or services to customer with high process flexibility or integration.Literatures on mass customization have been focused on mechanism of MC,but little on cus- tomer order decoupling point selection.The aim of this paper is to present a model for customer order decoupling point selection of domain knowledge interactions between enterprises and customers in mass customization.Based on the analysis of other researchers’ achievements combining the demand problems of customer and enterprise,a model of group decision for customer order decoupling point selection is constructed based on quality function deployment and multi-agent system.Considering relatively the decision mak- ers of independent functional departments as independent decision agents,a decision agent set is added as the third dimensionality to house of quality,the cubic quality function deployment is formed.The decision-making can be consisted of two procedures:the first one is to build each plane house of quality in various functional departments to express each opinions;the other is to evaluate and gather the foregoing sub-decisions by a new plane quality function deployment.Thus,department decision-making can well use its domain knowledge by ontology,and total decision-making can keep simple by avoiding too many customer requirements.
基金National Natural Science Foundation of China (No.59889505)
文摘The successful implementation of mass customization lies on reengineeringtechnology and management methods to organize the production. Especially in assembly phase, variousproduct configurations, due-time penalties and order-driven strategy challenge the traditionaloperation and management of assembly lines. The business features and the operation pattern ofassembly line based on mass customization are analyzed. And the research emphatically studiesvarious technologic factors to improve customer satisfaction and their corresponding implementmethods in operating assembly line. In addition, the models are proposed for operating assembly lineunder dynamic process environment in mass customization. A genetic approach is developed to providethe optimal solution to the models. The effectiveness of the proposed approach is evaluated with anindustrial application.
