Pub Date : 2016-07-10DOI: 10.1109/SOLI.2016.7551654
P. Jiang, Jiewu Leng, Kai Ding
Under the growing trend of personalization and socialization, social manufacturing is an emerging technical and business practice in mass individualization paradigm that allows prosumers to build personalized products and individualized services with their partners through integrating inter-organizational manufacturing service processes. This paper makes a comprehensive literature review and a further discussion on social manufacturing via a constructive methodology. After a clarification on definition of social manufacturing, we make an analysis on current research progress including the business models, implementations architectures and frameworks, case studies, and the key enabling techniques (e.g., big data mining and cyber-physical-social system) for realizing the idea of social manufacturing. The potential impact and future challenges are pointed out as well. It is expected that this review can help readers to gain more understanding on the idea of social manufacturing.
{"title":"Social manufacturing: A survey of the state-of-the-art and future challenges","authors":"P. Jiang, Jiewu Leng, Kai Ding","doi":"10.1109/SOLI.2016.7551654","DOIUrl":"https://doi.org/10.1109/SOLI.2016.7551654","url":null,"abstract":"Under the growing trend of personalization and socialization, social manufacturing is an emerging technical and business practice in mass individualization paradigm that allows prosumers to build personalized products and individualized services with their partners through integrating inter-organizational manufacturing service processes. This paper makes a comprehensive literature review and a further discussion on social manufacturing via a constructive methodology. After a clarification on definition of social manufacturing, we make an analysis on current research progress including the business models, implementations architectures and frameworks, case studies, and the key enabling techniques (e.g., big data mining and cyber-physical-social system) for realizing the idea of social manufacturing. The potential impact and future challenges are pointed out as well. It is expected that this review can help readers to gain more understanding on the idea of social manufacturing.","PeriodicalId":128068,"journal":{"name":"2016 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130401732","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 : 2016-07-10DOI: 10.1109/SOLI.2016.7551660
Akatsuki Ryu, Mark Nelson, Arja Mehtala, T. Nyberg, Gang-Yu Xiong
The Global Positioning System (GPS) technology has been widely used in many applications. However, GPS operation is very limited indoors. While people are spending most of the time indoor. Different solutions are used in indoor positioning and location based service. Indoor positioning based systems are increasingly used in manufacturing. Four instance indoor positioning systems are used for the assets tracking and human trajectory. Tracking mass amount of people Will generate huge big data, manufacturing companies as well as individuals can take advantage of this traffic flow data to pursue environmental, economic and social sustainable manufacturing strategies. In this paper, we describe one method of tracking massive amount of people and provide them and visual tracking information by using one of the indoor positioning Technologies HAIP provided by Nokia. We present empirical results of experiments of using the HAIP system.
{"title":"Non-GPS positioning sensor network in social manufacturing","authors":"Akatsuki Ryu, Mark Nelson, Arja Mehtala, T. Nyberg, Gang-Yu Xiong","doi":"10.1109/SOLI.2016.7551660","DOIUrl":"https://doi.org/10.1109/SOLI.2016.7551660","url":null,"abstract":"The Global Positioning System (GPS) technology has been widely used in many applications. However, GPS operation is very limited indoors. While people are spending most of the time indoor. Different solutions are used in indoor positioning and location based service. Indoor positioning based systems are increasingly used in manufacturing. Four instance indoor positioning systems are used for the assets tracking and human trajectory. Tracking mass amount of people Will generate huge big data, manufacturing companies as well as individuals can take advantage of this traffic flow data to pursue environmental, economic and social sustainable manufacturing strategies. In this paper, we describe one method of tracking massive amount of people and provide them and visual tracking information by using one of the indoor positioning Technologies HAIP provided by Nokia. We present empirical results of experiments of using the HAIP system.","PeriodicalId":128068,"journal":{"name":"2016 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133078400","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 : 2016-07-10DOI: 10.1109/SOLI.2016.7551671
Yuan-yuan Chen, Yisheng Lv
Urban traffic prediction is a critical component in intelligent transportation systems for both citizens and traffic management agencies. It is beneficial to know current and future traffic conditions prior a trip or a route for travelers. And it is also very helpful for proactive traffic management for transportation administrative sectors. In this paper, we apply classification techniques to forecast traffic conditions based on categorical data collected from open web maps. To this end, we first collect traffic condition data from AMAP which is a web map, navigation and location based services provider in China. Then we primarily analyze AMAP data with trend analysis and power spectrum analysis. Finally, we employ random walk, naïve Bayes, decision tree and support vector machine methods to forecast traffic conditions in the future based on historical and current conditions. Experimental results demonstrate that it is feasible to make forecast on traffic conditions with reasonable accuracy.
{"title":"Analysis and forecasting of urban traffic condition based on categorical data","authors":"Yuan-yuan Chen, Yisheng Lv","doi":"10.1109/SOLI.2016.7551671","DOIUrl":"https://doi.org/10.1109/SOLI.2016.7551671","url":null,"abstract":"Urban traffic prediction is a critical component in intelligent transportation systems for both citizens and traffic management agencies. It is beneficial to know current and future traffic conditions prior a trip or a route for travelers. And it is also very helpful for proactive traffic management for transportation administrative sectors. In this paper, we apply classification techniques to forecast traffic conditions based on categorical data collected from open web maps. To this end, we first collect traffic condition data from AMAP which is a web map, navigation and location based services provider in China. Then we primarily analyze AMAP data with trend analysis and power spectrum analysis. Finally, we employ random walk, naïve Bayes, decision tree and support vector machine methods to forecast traffic conditions in the future based on historical and current conditions. Experimental results demonstrate that it is feasible to make forecast on traffic conditions with reasonable accuracy.","PeriodicalId":128068,"journal":{"name":"2016 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128282970","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 : 2016-07-10DOI: 10.1109/SOLI.2016.7551680
Yingying Ma, Xiaoran Qin, Jian-min Xu, Wenjing Wang
The dispatching policy of public bicycles during peak hours largely determines the sharing rate of bicycles and service level of public bicycle system. Firstly, a dynamic demand prediction model of public bicycle system is proposed considering reservation data and historical data. Secondly, a hierarchical dispatching policy and network partitioning method are discussed. Thirdly, an optimization model with time window to decide the number of bicycles that need to be dispatched is put forward considering the cost of dispatching and waiting time of passengers, and the method to decide the path of dispatching is also discussed. Finally, a case study in Guangzhou shows that the proposed policy could provide lower waiting time for passengers and better bicycle sharing rate of bicycles.
{"title":"A hierarchical public bicycle dispatching policy for dynamic demand","authors":"Yingying Ma, Xiaoran Qin, Jian-min Xu, Wenjing Wang","doi":"10.1109/SOLI.2016.7551680","DOIUrl":"https://doi.org/10.1109/SOLI.2016.7551680","url":null,"abstract":"The dispatching policy of public bicycles during peak hours largely determines the sharing rate of bicycles and service level of public bicycle system. Firstly, a dynamic demand prediction model of public bicycle system is proposed considering reservation data and historical data. Secondly, a hierarchical dispatching policy and network partitioning method are discussed. Thirdly, an optimization model with time window to decide the number of bicycles that need to be dispatched is put forward considering the cost of dispatching and waiting time of passengers, and the method to decide the path of dispatching is also discussed. Finally, a case study in Guangzhou shows that the proposed policy could provide lower waiting time for passengers and better bicycle sharing rate of bicycles.","PeriodicalId":128068,"journal":{"name":"2016 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130650311","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 : 2016-07-10DOI: 10.1109/SOLI.2016.7551661
G. Xiong, Aping Zhao, T. Nyberg, Gang-Yu Xiong
A success of an improvement project on solving a problem in an organization is not only depending an appropriate methodology on problem solving with Lean, TOC or 6 sigma with relevant tools, but also it is very important to have an appropriate methodology and process on change management integrated with project management during the improvement project. This paper describes the principle of change management based on existing literature, and illustrates a case study on how an improvement project apply theory and methodology of change management to make successful change. Firstly, the literature review relevant to concerns for support change in a business environment is introduced. General tools, models, and solutions to make a change effectively in an organization are explained. Next one framework with relevant tools and models are selected to the case study that conducts a manufacturing with ETO (Engineering-to-order) product. Next regarding the readiness for change, and the implementation of the change the paper introduces how the selected framework and the tools and models on change management is integrated with project management during different phases of the improvement project. As a result, it shows a success both from improvement project and change management perspective. In particular, achievement in the change management is not only showing the successful improvement project, but also the organization realizes another great positive change - people's improved behavior on daily work. Hence a long-term benefit from the improvement project and change management is gained. The achievement shows that similar approach on change management in an organization may be applied to more organizations.
{"title":"Change management on improvement project for success","authors":"G. Xiong, Aping Zhao, T. Nyberg, Gang-Yu Xiong","doi":"10.1109/SOLI.2016.7551661","DOIUrl":"https://doi.org/10.1109/SOLI.2016.7551661","url":null,"abstract":"A success of an improvement project on solving a problem in an organization is not only depending an appropriate methodology on problem solving with Lean, TOC or 6 sigma with relevant tools, but also it is very important to have an appropriate methodology and process on change management integrated with project management during the improvement project. This paper describes the principle of change management based on existing literature, and illustrates a case study on how an improvement project apply theory and methodology of change management to make successful change. Firstly, the literature review relevant to concerns for support change in a business environment is introduced. General tools, models, and solutions to make a change effectively in an organization are explained. Next one framework with relevant tools and models are selected to the case study that conducts a manufacturing with ETO (Engineering-to-order) product. Next regarding the readiness for change, and the implementation of the change the paper introduces how the selected framework and the tools and models on change management is integrated with project management during different phases of the improvement project. As a result, it shows a success both from improvement project and change management perspective. In particular, achievement in the change management is not only showing the successful improvement project, but also the organization realizes another great positive change - people's improved behavior on daily work. Hence a long-term benefit from the improvement project and change management is gained. The achievement shows that similar approach on change management in an organization may be applied to more organizations.","PeriodicalId":128068,"journal":{"name":"2016 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125663003","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 : 2016-07-10DOI: 10.1109/SOLI.2016.7551690
Ran Tao, Y. Xi, Dewei Li
With the rapid development of economy, the number of vehicles grows, and traffic congestion occurs widely. Improving the condition of traffic congestion is urgent. The aim of this paper was to analyze the relationship between links and explore how they influence congestion propagation. Based on the existing Cell Transmission Model (CTM) theory, we had a lot of simulation under various circumstances through the program, in which the Average Journey Velocity (AJV) is selected as a measurement of the degree of link congestion. We established Link State Graph which is a directed network graph regarding links as nodes to observe the relationship between links. At last, we concluded how the location and adjacent links of a link can influence congestion propagation with the Link State Graph.
{"title":"Simulation analysis on urban traffic congestion propagation based on complex network","authors":"Ran Tao, Y. Xi, Dewei Li","doi":"10.1109/SOLI.2016.7551690","DOIUrl":"https://doi.org/10.1109/SOLI.2016.7551690","url":null,"abstract":"With the rapid development of economy, the number of vehicles grows, and traffic congestion occurs widely. Improving the condition of traffic congestion is urgent. The aim of this paper was to analyze the relationship between links and explore how they influence congestion propagation. Based on the existing Cell Transmission Model (CTM) theory, we had a lot of simulation under various circumstances through the program, in which the Average Journey Velocity (AJV) is selected as a measurement of the degree of link congestion. We established Link State Graph which is a directed network graph regarding links as nodes to observe the relationship between links. At last, we concluded how the location and adjacent links of a link can influence congestion propagation with the Link State Graph.","PeriodicalId":128068,"journal":{"name":"2016 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129262681","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}
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