A data-driven scheduling approach to smart manufacturing

TLDR: A data-driven architecture for scheduling, in which the system has real time access to data and decisions can be made ahead of time, on the basis of more information, based on the architecture of cyber-physical systems.

About: This article is published in Journal of Industrial Information Integration.The article was published on 2019-09-01 and is currently open access. It has received 69 citations till now. The article focuses on the topics: Dynamic priority scheduling & Scheduling (production processes).

Frequently asked questions

Q1. What are the contributions mentioned in the paper "A data-driven scheduling approach to smart manufacturing" ?

On these grounds the authors propose a data-driven architecture for scheduling, in which the system has real time access to data. This promising approach is based on the architecture of cyber-physical systems, with a data-driven engine that uses, in particular, Big Data techniques to extract vital information for Industry 4. 0 systems. 

Q2. What is the way to solve the problem of a variety of products?

With a variety of products and short production cycles, the velocity of generation of data will be fast, while if the products are few or modular it might be slower. 

Q3. What can be done to improve the search in databases?

AI techniques can be applied to improve searches in databases as well as to use those results to correct errors detected in the analysis of patterns of behaviour of the system. 

Q4. What is the main reason for the difficulties in the data flow?

The data flow may face obstacles because of the traditional design of machines and other production assets, more ready to receive orders than to provide information. 

Q5. What is the way to improve the data analysis step?

TThe data analysis step can be improved by means of the use of CPPS, thanks oftheir connection to high performance computing centres through cloud computing. 

Q6. What is the purpose of the DSS?

Their DSS based on these potentialities of CPPS is intended as a step towards implementing the aforementioned vertical integration in Smart Manufacturing environments. 

Q7. What is the level of CPPS that is important for the development of Industry 4.0?

given the computing power of CPPS, they will also be able to plan, evaluate and manage the entire production process (level 3). 

Q8. What are the important aspects that arise in a scheduling context?

Important aspects that arise in a scheduling context are the costs of the different assignments, the delays in deliverance, product quality, etc. 

Q9. What is the value of the data that can be safely discarded?

the marginal value of data (which indicate what data can be safely discarded) required for the direct solution of the scheduling problem (Figures 2 and 3) is high, while the rest of the data that arise in the vertical and horizontalAC CEPT EDM ANUS CRIP Tintegration of the system has a high aggregate value, due to their influence in increasing the flexibility and efficiency of the system. 

Q10. What are the main design levels of CPS?

They define a 5C architecture outlining the main design levels of CPS: 1) Connection level, 2) Conversion level, 3) Cyber level, 4) Cognition level and 5) Configuration level.