An agent-based approach for dependable planning of production sequences in automated production systems

2017 ◽  
Vol 65 (11) ◽  
Author(s):  
Sebastian Rehberger ◽  
Lucas Spreiter ◽  
Birgit Vogel-Heuser

AbstractOne approach to achieve flexibility and dependability for the control of automated production systems (aPS) is agent-oriented software engineering (AOSE). In this paper, the modular decoupling of the supervisory control, most significantly the planning of production sequences and transfer routes, from the distributed real-time control of the plant resources is demonstrated by the use of agents. The resulting product management agent (PMA) represents the technical process of the manufactured product and conducts a discrete reasoning algorithm to derive appropriate production plans by the use of graph-search and also by interaction with the underlying resource agents (RA). It is shown, that for a given production system, dependable solutions are automatically generated in regard to a given product recipe. Further it is deduced, that the solutions are calculated and evaluated by the PMA within a deterministic time duration. This is argued on the fact, that the computation complexity does not exceed polynomial time and is mostly predetermined by the design parameters of the plant. Thus, it gives a reasonable approach for the use in a real-time environment. Additionally, through separation of supervisory and field control, a modular software engineering is achieved, offering the advantage that the PMA and the resource agents can be reused, by solely adapting the knowledge bases and without the need for modifying the planning algorithms after a reconfiguration of the aPS.

2018 ◽  
Vol 66 (10) ◽  
pp. 784-794 ◽  
Author(s):  
Jakob Mund ◽  
Safa Bougouffa ◽  
Iman Badr ◽  
Birgit Vogel-Heuser

Abstract Continuous integration (CI) is widely used in software engineering. The observed benefits include reduced efforts for system integration, which is particularly appealing for engineering automated production systems (aPS) due to the different disciplines involved. Yet, while many individual quality assurance means for aPS have been proposed, their adequacy for and systematic use in CI remains unclear. In this article, the authors provide two key contributions: First, a quality model for a model-based engineering approach specifically developed for aPS. Based thereon, a discussion of the suitable verification techniques for aPS and their systematic integration in a CI process are given. As a result, the paper provide a blueprint to be further studied in practice, and a research agenda for quality assurance of aPS.


2009 ◽  
pp. 773-796
Author(s):  
Manuel Kolp ◽  
Stéphane Faulkner ◽  
Yves Wautelet

Multi-agent systems (MAS) architectures are gaining popularity over traditional ones for building open, distributed, and evolving software required by today’s corporate IT applications such as e-business systems, Web services, or enterprise knowledge bases. Since the fundamental concepts of multi-agent systems are social and intentional rather than object, functional, or implementationoriented, the design of MAS architectures can be eased by using social patterns. They are detailed agent-oriented design idioms to describe MAS architectures composed of autonomous agents that interact and coordinate to achieve their intentions, like actors in human organizations. This article presents social patterns and focuses on a framework aimed to gain insight into these patterns. The framework can be integrated into agent-oriented software engineering methodologies used to build MAS. We consider the Broker social pattern to illustrate the framework. An overview of the mapping from system architectural design (through organizational architectural styles), to system detailed design (through social patterns), is presented with a data integration case study. The automation of creating design patterns is also discussed.


2021 ◽  
Author(s):  
Birgit Vogel-Heuser ◽  
Juliane Fischer ◽  
Eva-Maria Neumann ◽  
Matthias Kreiner

Abstract The amount of software in automated production systems, including its development effort, is continuously increasing to currently up to 35-50% of the development personnel. Consequently, success factors for achieving modularity and complexity management of control software are of high economic interest. Scientific solutions are manifold but often not implemented in industry. This paper introduces the study QoaPS SWE (Quality of automated Production Systems’ Software Engineering) providing insights into 61 machine and plant manufacturing companies to give quantitative and qualitative results to five essential research questions on success factors in the design of field-level control code. Compared to preceding surveys, QoaPS SWE achieves statistically significant results for software maturity (MMOD+), complexity, and model-based software engineering and provides detailed insights into causes and consequences for single criteria, thus clearly identifying obstacles to be addressed in future research and with industrial countermeasures. Especially staff qualification and organizational issues are identified as obstacles to applying the object-oriented programming paradigm for control software in machine and plant manufacturing. Validity is ensured by analyzing the statistical significance of the results in addition to comparisons with earlier surveys and interviews as well as the comparison with already existing and accepted maturity levels. The provided qualitative and quantitative results will allow the benchmarking of companies’ maturity and the derivation of concrete recommendations for companies depending on their MMOD+ value and the evaluated characteristics.


IEE Review ◽  
1992 ◽  
Vol 38 (3) ◽  
pp. 112
Author(s):  
Stuart Bennett

2021 ◽  
Vol 13 (3) ◽  
pp. 1081
Author(s):  
Yoon Kyung Lee

Technologies that are ready-to-use and adaptable in real time to customers’ individual needs are influencing the supply chain of the future. This study proposes a supply chain framework for an innovative and sustainable real-time fashion system (RTFS) between enterprises, designers, and consumers in 3D clothing production systems, using information communication technology, artificial intelligence (AI), and virtual environments. In particular, the RTFS is targeted at customers actively involved in product purchasing, personalising, co-designing, and manufacturing planning. The fashion industry is oriented towards 3D services as a service model, owing to the automation and democratisation of product customisation and personalisation processes. Furthermore, AI offers referral services to prosumers or/and customers and companies, and proposes individual designs with perfect styles and measurements using new 3D computer aided design and AI-based product design technologies for fashion and design companies and customers. Consequently, 3D fashion products in the RTFS supply chain are entirely digital, saving time and money with sampling and tracking capabilities, secured, and trusted with personalised service delivery.


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