This paper presents the design and prototype implementation of a service-based control system responsible for the material supply operations planning and coordination in assembly lines. The material supply processes are carried out by autonomous mobile units that are responsible for the transportation of the consumables from the warehouse to the production stations. The plan generation based on time and inventory level driven criteria is automatically carried out by a web-based software that can also distribute the derived plan to the autonomous mobile units. The proposed system was implemented on a case inspired by an actual production line from the automotive assembly sector. Discrete event simulation has been employed for the investigated production system, to derive the specifications for the mobile units (e.g. number of boxes that can carry simultaneously) that may serve the system efficiently. The results indicate that the proposed architecture integrated with the discussed mobile assistant units may provide high quality solutions with respect to the end user criteria.

The Human Robot Collaborative (HRC) workplace design and the automatic task allocation can significantly decrease the time of a new set-up or a cell's reconfiguration. This paper proposes a method for an HRC workplace layout generation and the preliminary assignment of human and robot tasks. A decision making framework is proposed in order for the location of all components in the available layout space to be decided upon. The evaluation of the alternative HRC workplace layouts is based on multiple criteria. The system has been integrated with a user interface into a 3D simulation tool and tested on an automotive industry case study

Providing an integrated Product-Service System (PSS) supported by Cyber-Physical Systems (CPS), as a smart solution, is increasingly offered by industrial machinery. In this approach, instead of providing products with after-sale services, the value proposition is mostly based on guaranteeing a trustable operation. As a result, capturing and analyzing information from a machine’s condition during its lifespan becomes an essential part of the smart PSS. Enabling this through lifecycle monitoring, sensing devices are at the core of smart PSS. Thus, the optimal configuration of PSS components is a critical step to ensure the efficiency of the solution. PSS design challenges arise because of the differences between characteristics and specifications of the embedded sensing system and the product. To fulfill this challenge, knowledge extraction and reuse from these domains is crucial during the design process. To do so, a sensor ontology is used as the backbone of the PSS knowledge-based framework. The focus of this paper is on defining the embedded sensing systems tailored to industrial PSS and the use of these systems in providing customized services. As part of the ICP4Life platform, the paper presents a sensing system ontology as a framework to support the smart services in industrial machinery PSS. An industrial use case is conducted to validate the efficiency of the proposed ontology and to show the benefits of the ICP4Life platform to reduce time and cost of PSS development processes.