ABSTRACT
Automation and the use of robotic components within business processes is in vogue across retail and manufacturing industries. However, a structured way of analyzing performance improvements provided by automation in complex workflows is still at a nascent stage. In this paper, we consider the common Industry 4.0 automation workflow resource patterns and model them within a hybrid queuing network. The queuing stations are replaced by scale up, scale out and hybrid scale automation patterns, to examine improvements in end-to-end process performance. We exhaustively simulate the throughput, response time, utilization and operating costs at higher concurrencies using Mean Value Analysis (MVA) algorithms. The queues are analyzed for cases with multiple classes, batch/transactional processing and load dependent service demands. These solutions are demonstrated over an exemplar use case of automation in Industry 4.0 warehouse automation workflows. A structured process of automation workflow performance analysis will prove valuable across industrial deployments.
- P. Leita, A. W. Colombo & S. Karnouskos, Industrial automation based on cyber-physical systems technologies: Prototype implementations and challenges", Computers in Industry, vol. 81, pp. 11--25, 2016. Google ScholarDigital Library
- S. Greengard, "The Internet of Things", MIT, 2015. Google ScholarDigital Library
- M. Hermann, T. Pentek & B. Otto, "Design Principles for Industrie 4.0 Scenarios", 49th Hawaii Intl. Conf. on System Sciences, 2016. Google ScholarDigital Library
- S. Russell & P. Norvig, "Artificial Intelligence: A Modern Approach", Pearson, 3rd Ed., 2009. Google ScholarDigital Library
- J. Bartholdi & S. Hackman, "Warehouse and Distribution Science", The Supply Chain and Logistics Institute, 2016.Google Scholar
- P. Wurman, R. D'Andrea & M. Mountz, "Coordinating Hundreds of Cooperative, Autonomous Vehicles in Warehouses", AAAI Artificial Intelligence Mag., vol. 29, no. 1, pp. 9--19, 2008.Google ScholarDigital Library
- M, Weske, "Business Process Management: Concepts, Languages, Architectures", Springer-Verlag Berlin Heidelberg, 2nd ed., 2012. Google ScholarDigital Library
- Hao Zhang et al., "DoraPicker: An autonomous picking system for general objects", IEEE Intl. Conf. on Automation Science and Engineering (CASE), pp. 721--726, 2016.Google Scholar
- N. Russell, A.H.M. ter Hofstede, D. Edmond & W.M.P. van der Aalst, "Workflow Resource Patterns", BETA Working Paper Series -- Eindhoven University of Technology, WP 127, 2004.Google Scholar
- E. Lazowska, J. Zahorjan, S. Graham & K. Sevcik, "Quantitative System Performance: Computer System Analysis Using Queuing Network Models", Prentice-Hall, Inc., 1984. Google ScholarDigital Library
- R. Ganeshan, "Managing supply chain inventories: A multiple retailer, one warehouse, multiple supplier model", Int. J. Production Economics, vol. 59, pp. 341--354, 1999.Google ScholarCross Ref
- M. K. Govil & M. C. Fu, "Queuing theory in manufacturing: A survey", J. of Manufacturing Sys., vol. 18, no. 3, pp. 214--240, 1999.Google ScholarCross Ref
- B. Schroeder, A. Wierman & M. Harchol-Balter, "Open Versus Closed: A Cautionary Tale", USENIX NSDI Tech. Paper, 2006. Google ScholarDigital Library
- T. Lorido-Botran, J. Miguel-Alonso & J. Lozano, "A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments", vol. 12, no. 4, pp. 559--592, 2014. Google ScholarDigital Library
- A. Kattepur, S. Dey & P. Balamuralidhar, "Knowledge Based Hierarchical Decomposition of Industry 4.0 Robotic Automation Tasks", IEEE Intl. Conf. on Industrial Electronics, 2018.Google Scholar
- A. Kattepur & M. Nambiar, "Performance Modeling of Multi-tiered Web Applications with Varying Service Demands", IPDPS Workshops, 2015. Google ScholarDigital Library
- F. Basile, P. Chiacchio & J. Coppola, "A hybrid model of complex automated warehouse systems -- Part I: Modeling and simulation", IEEE Trans. on Automation Science and Engineering, vol. 9, no. 4, 2012.Google Scholar
- J. C. Hernandez-Matias, A. Vizan, J. Perez-Garcia & J. Rios, "An integrated modelling framework to support manufacturing system diagnosis for continuous improvement", Robotics and Computer-Integrated Manufacturing, vol. 24, pp. 187--199, 2008. Google ScholarDigital Library
- W.M.P. van der Aalst, "Verification of Workflow Nets", Intl. Conf. on Application and Theory of Petri Nets, 1997. Google ScholarDigital Library
- M. Kovacs and L. Gonczy, "Simulation and Formal Analysis of Workflow Models", Electronic Notes in Theoretical Computer Science, vol. 211, pp. 221--230, 2008. Google ScholarDigital Library
- A. Kattepur, A. Mukherjee & P. Balamuralidhar, "Verification and Timing Analysis in Industry 4.0 Warehouse Automation Workflows", IEEE Intl. Conf. on Emerging Technologies and Factory Automation, 2018.Google Scholar
Index Terms
- Towards Structured Performance Analysis of Industry 4.0 Workflow Automation Resources
Recommendations
The analysis of batch sojourn-times in polling systems
We consider a cyclic polling system with general service times, general switch-over times, and simultaneous batch arrivals. This means that at an arrival epoch, a batch of customers may arrive simultaneously at the different queues of the system. For ...
Heavy traffic analysis of polling models by mean value analysis
In this paper we present a new approach to derive heavy-traffic asymptotics for polling models. We consider the classical cyclic polling model with exhaustive or gated service at each queue, and with general service-time and switch-over time ...
Polling systems with a gated/exhaustive discipline
ValueTools '08: Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and ToolsWe consider a polling system where the server cyclically serves the queues according to the following discipline: the server does one round of visits to the queues applying the gated service discipline at each of the queues, followed by one round of ...
Comments