A smart palletising planning and control model in Logistics 4.0 framework

Abstract

The paper describes a smart model for palletising as main intra-logistics task for product-on-pallet distribution, and its development in Logistics 4.0 framework aligned to Industry 4.0. The model is developed in holonic paradigm as a 2-layer Holonic Logistics Execution System (HLES) in semi-heterarchical topology. Scheduling of logistics activities and allocation to resources are optimised for global efficiency on compact time periods. The logistics model virtualises physical entities: resources, pallets and orders as holons implemented with digital twin software, and categories of task workloads: resource health monitoring, dispatching and tracking pallet orders, re-assigning jobs at resource failure, which grants reality-awareness and robustness. Global workload optimisation uses Constraint Programming as decision making technology with ILOG optimiser engine as situation-specific solver tool in SaaS cloud model, and delegate multi-agent system (MAS) technology for intelligence distribution. The optimised objective function is a combination of palletising cost weighted by robot speed limits and pallet storage cost in payable stocks. The main constructs are exemplified and validated on a real-life structure with multiple palletising resources in which programmable logic controllers (PLC) coordinate locally the parallel execution of order holons according to their globally optimised sequence.

KEYWORDS:

• Integrated logistics engineering
• advanced planning and scheduling systems
• palletising
• combinatorial optimisation
• distributed MAS

Acknowledgement

The initial research concerning the application of the holonic paradigm to the supervisory control of Logistics Execution Systems (LES) using virtualisation techniques has been reported in Borangiu, Răileanu, and Stan (2022).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available at the online FTP repository http://141.85.239.9/IJPR_data_Borangiu_Raileanu.xls, within this article. This material represents an Excel file with sheets containing input data, fixed and variable solutions, and the data centralised in Table 2.

Additional information

Notes on contributors

Theodor Borangiu

Theodor Borangiu is full professor at University Politehnica of Bucharest, Faculty of Automatic Control and Computers since 1991. He teaches courses in manufacturing control, robot vision, and microcontrollers. His areas of interest are: distributed automation, digital manufacturing control and robot-vision. He has expertise in cloud manufacturing, service-oriented, holonic and multi-agent manufacturing control, and visual servoing of robots. He is author of 43 books and more than 300 peer reviewed articles.

Silviu Răileanu

Silviu Răileanu is associate professor at University Politehnica Bucharest, Faculty of Automatic Control and Computers. He oversees the courses: Supply Chain Management and Logistics, Multi-agent Systems for enterprise control, and Information systems for production management. His scientific interests include: distributed intelligence for automation systems, agent orientation in industry and services, virtualised HMES, supply chain optimisation, cloud manufacturing.