Stream-IT: Continuous and dynamic processing of production systems data - Throughput bottlenecks as a case-study
Paper in proceeding, 2019

Considering the needs for continuous availability of information out of data generated in Cyber-Physical production systems, we investigate the use of continuous stream processing as a paradigm for generating useful information out of the data, to support efficient and safe operation, as well as planning activities.Our contributions and expected benefits: (i) we show possibilities to automate and pipeline the validation and analysis of the data, hence providing an automated way to improve the quality of the latter and parallelizing the two phases; (ii) we show how to induce lower latency in generating the desired information, enabling it to be continuously made available, before whole batches of data are gathered, in cost-efficient ways; (iii) besides the automation of the above procedures that are commonly done in a batch fashion and with significant manual effort by the production system analysts, we show additional options for configuring ways in which to automate deeper analysis of the data; in particular, we provide evidences about how the rich semantics of stream processing frameworks can ease the development and deployment of data analysis applications in production systems.Moreover, using the problem of bottleneck detection as a sample scenario, we illustrate the above in a concrete fashion, on cost-efficient systems, that are plausible to have in existing deployments. The experimental study is on a 2-year data-set with more than 8.5 million entries, from a system including more than 30 interconnected machines and it demonstrates the benefits of the proposed methods, in providing timely and multidimensional information from the data, enabling possibilities for deeper analyses.

Author

Hannaneh Najdataei

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Mukund Subramaniyan

Chalmers, Industrial and Materials Science, Production Systems

Vincenzo Massimiliano Gulisano

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Anders Skoogh

Chalmers, Industrial and Materials Science, Production Systems

Marina Papatriantafilou

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

IEEE International Symposium on Industrial Electronics

Vol. 2019-June 1328-1333 8781203
978-172813666-0 (ISBN)

28th IEEE International Symposium on Industrial Electronics, ISIE 2019
Vancouver, Canada,

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Subject Categories

Other Computer and Information Science

Computer Science

Computer Systems

DOI

10.1109/ISIE.2019.8781203

More information

Latest update

1/10/2020