Towards Adaptive Discrete Event Control Based on PRD, PSS and Automatic Planner

2020 ◽  
Author(s):  
Gabriel De Almeida Souza ◽  
José Jean-Paul Zanlucchi de Souza Tavares ◽  
José Reinaldo Silva

Industry 4.0 technologies integrate devices and data, bring exibility, eciency and decision making, derived from decentralization. In a post pandemic society it is mandatory to reduce human presence in production and distribution of goods. This work implements some of Industry 4.0 characteristics by combining manufacturing elements such as Cyber Physical System (CPS) with passive entities that directly aect decisions in the same automatic planning domain. Theproposal is illustrated by emulating a Block World problem, where it will be used a set of blocks with Radio Frequency Identication (RFID) each one containing its self goals, represented by predicates, an approach called PRD (Predicate inside RFID Database). A robot can identify objects by helding a RFID reader integrated with a Physical State Space (PSS). Since the robot controller has a local view of the process it is unable to compute the plan for the whole systemby itself, so the planning process must be a Cloud service. Local planning must also be taken into consideration, solving any network issues. Thus, a generic solution has to be adapted to t physical execution and domain constraints. Such solution detects changes in the physical environment and redo its plan, generating an adaptive discrete event controller. 

2020 ◽  
Vol 2020 ◽  
pp. 1-19 ◽  
Author(s):  
César Martínez-Olvera

It has been stated that Industry 4.0’s goal is, among others, the sustainable success in a market characterized by exigent and informed consumers demanding personalized products and services, where the level of manufacturing complexity increases with level of product customization. Even though different manufacturing complexity measures have been developed, there seems to be a lack of a comprehensive metric that address both the mass customization variety-induced complexity, and the complexity derived from the adoption of the Industry 4.0 paradigm. The main original contribution of this paper is the development of an entropy-based (entropic) formulation to address this last issue. Its validity and usefulness is put to the test via a discrete-event simulation study of a mass customization production system operating within an Industry 4.0 context. Our findings show that the entropic formulation acts as a fairly good trend indicator of the system’s performance parameter increase/decrease, but not as an estimator of the final values. A discussion of the managerial implications of the obtained results is offered at the end of the paper.


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