2020年11月18日星期三

ASQ Webinar - Managing for Quality Amidst Digital Turbulence

ASQ Quality Management Division arranged a Webinar session and session #12 named “Managing for Quality Amidst Digital Turbulence” on 17th Nov 2020.  This webinar aimed to illustrate how quality management could be presented as a viable methodology in the emerging digital age and how transformation would be necessary to address changing priorities. Dr. Gregory H. Watson was the guest speaker.  Firstly, he briefed some major implications for quality.


Then Dr. Watson introduced Quality 4.0 that is the digitalization of quality.  Its application separated into three key areas and they were digital technologies, productive system and profound knowledge.  Two applications were discussed and they were leveraging digital technologies (e.g. AI, ML/DL, Neural Networks, Blockchain and Augmented Reality, etc.) and integrating productive systems (e.g. H/W & S/W mechanisms of production, information, data collection, etc.) so as to improve productivity and reduce human error.


And then he explained the objective to obtain profound knowledge that had four dimensions and they were “Structure of Systems”, “Statistical Thinking about Process Variation”, “Learning to Develop Knowledge” and “Psychological Impact”.  Dr. Watson also explained how quality activities supported digitalization 


After that Dr. Watson discussed the production system as thinking system. Digital Twin models were employed for operation system.  


He also introduced some technology areas included in Quality 4.0.  It started from data flows and using technology to learning and applying that data implication.


He then mentioned the data clouds which separated by external public cloud and internal private cloud.  We observed that QMS to be performed between two clouds for data integration, alignment and predication.  


Finally, Dr. Watson reviewed the essential four steps of information quality criteria from inclusiveness to integrity to intensity and then to insight.  However, we needed to avoid the cost of bad data!.  


Lastly, Dr. Watson concluded Quality 4.0 challenges that we needed to understand and accept such challenges. That included technological change, process design question, system engineering the integration of novel technologies in existing operation system, etc. 

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