P-SaaS: knowledge service oriented manufacturing workflow model for knowledge collaboration and reuse*

Orders come and go, but for manufacturing enterprises product-related production problems (PPs) are forever. To realize the aim of CTQS (i.e., lower cost, faster time to market, higher quality and better service), a serviced oriented model of product related problem-solving as a service (P-SaaS) is presented with three-layer structure: task bade workflow layer, knowledge based solution layer and cognition based decision-making layer in this paper. For knowledge oriented PPs solving, each task/subtask is taken as a piece of knowledge service, and the function based task decision for problem solving is organized and implemented by independent Web applications on the microservice architecture platform. Each application is considered as an agent based on its independent function. To support this model, operational models and key enable technologies are detailed. Firstly, a task based workflow is constructed to orchestrate the meta-events of specific task through coordination agent. Secondly, focused on a specific task of PPs query, a similarity based knowledge flow is proposed to retrieve the finite set of alternative solutions with a set threshold value through core agent. Thirdly, a cognition based decision synthesis flow is used to improve the quality of alternative solutions by knowledge collaboration and fusion through the individual agent. Finally, a case on high voltage apparatus in XD company is introduced to validate the proposed models.

[1]  Yanbo Han,et al.  Service Mesh: Challenges, State of the Art, and Future Research Opportunities , 2019, 2019 IEEE International Conference on Service-Oriented System Engineering (SOSE).

[2]  Brigitte Chebel-Morello,et al.  Reutilization of diagnostic cases by adaptation of knowledge models , 2013, Eng. Appl. Artif. Intell..

[3]  Sheng-Tun Li,et al.  Using mutually validated memories of experts for case-based knowledge systems , 2015, Knowl. Based Syst..

[4]  Enya Kong Tang,et al.  Learning to extract domain-specific relations from complex sentences , 2016, Expert Syst. Appl..

[5]  Yang Zhang,et al.  A Cross-Layer Security Solution for Publish/Subscribe-Based IoT Services Communication Infrastructure , 2017, 2017 IEEE International Conference on Web Services (ICWS).

[6]  Yang Gao,et al.  Multistream Classification with Relative Density Ratio Estimation , 2019, AAAI.

[7]  Klaus-Dieter Althoff,et al.  Knowledge-based multi-agent system for manufacturing problem solving process in production plants , 2018 .

[8]  Weihua Gui,et al.  A Data and Knowledge Collaboration Strategy for Decision-Making on the Amount of Aluminum Fluoride Addition Based on Augmented Fuzzy Cognitive Maps , 2019 .

[9]  Pingyu Jiang,et al.  Manufacturing Knowledge Graph: A Connectivism to Answer Production Problems Query With Knowledge Reuse , 2019, IEEE Access.

[10]  A Security Framework for Scientific Workflow Provenance Access Control Policies , 2019, IEEE Transactions on Services Computing.

[11]  Dawn M. Tilbury,et al.  Production as a Service: A Digital Manufacturing Framework for Optimizing Utilization , 2018, IEEE Transactions on Automation Science and Engineering.

[12]  Boonserm Kulvatunyou,et al.  On architecting and composing through-life engineering information services to enable smart manufacturing , 2014 .

[13]  Philippe Smets,et al.  Decision making in the TBM: the necessity of the pignistic transformation , 2005, Int. J. Approx. Reason..

[14]  Victor B. Kreng,et al.  The application of Fuzzy Delphi Method and Fuzzy AHP in lubricant regenerative technology selection , 2010, Expert Syst. Appl..

[15]  Pingyu Jiang,et al.  A framework for planing and solving production problems with manufacturing knowledge reuse , 2019, 2019 IEEE International Conference on Smart Manufacturing, Industrial & Logistics Engineering (SMILE).