Maintainability and evolvability of control software in machine and plant manufacturing -- An industrial survey

Automated Production Systems (aPS) have lifetimes of up to 30-50 years, throughout which the desired products change ever more frequently. This requires flexible, reusable control software that can be easily maintained and evolved. To evaluate selected criteria that are especially relevant for maturity in software maintainability and evolvability of aPS, the approach SWMAT4aPS+ builds on a questionnaire with 52 questions. The three main research questions cover updates of software modules and success factors for both cross-disciplinary development as well as reusable models. This paper presents the evaluation results of 68 companies from machine and plant manufacturing (MPM). Companies providing automation devices and/or engineering tools will be able to identify challenges their customers in MPM face. Validity is ensured through feedback of the participating companies and an analysis of the statistical unambiguousness of the results. From a software or systems engineering point of view, almost all criteria are fulfilled below expectations

Increasing System Test Coverage in Production Automation Systems

An approach is introduced, which supports a testing technician in the identification of possibly untested behavior of control software of fully integrated automated production systems (aPS). Based on an approach for guided semi-automatic system testing, execution traces are recorded during testing, allowing a subsequent coverage assessment. As the behavior of an aPS is highly dependent on the software, omitted system behavior can be identified and assessed for criticality. Through close cooperation with industry, this approach represents the first coverage assessment approach for system testing in production automation to be applied on real industrial objects and evaluated by industrial experts

Industrially Applicable System Regression Test Prioritization in Production Automation

When changes are performed on an automated production system (aPS), new faults can be accidentally introduced in the system, which are called regressions. A common method for finding these faults is regression testing. In most cases, this regression testing process is performed under high time pressure and on-site in a very uncomfortable environment. Until now, there is no automated support for finding and prioritizing system test cases regarding the fully integrated aPS that are suitable for finding regressions. Thus, the testing technician has to rely on personal intuition and experience, possibly choosing an inappropriate order of test cases, finding regressions at a very late stage of the test run. Using a suitable prioritization, this iterative process of finding and fixing regressions can be streamlined and a lot of time can be saved by executing test cases likely to identify new regressions earlier. Thus, an approach is presented in this paper that uses previously acquired runtime data from past test executions and performs a change identification and impact analysis to prioritize test cases that have a high probability to unveil regressions caused by side effects of a system change. The approach was developed in cooperation with reputable industrial partners active in the field of aPS engineering, ensuring a development in line with industrial requirements. An industrial case study and an expert evaluation were performed, showing promising results.Comment: 13 pages, https://ieeexplore.ieee.org/abstract/document/8320514

Towards a Formal Specification Framework for Manufacturing Execution Systems

Manufacturing Execution Systems (MES) optimize production and business processes at the same time. However, the engineering and specification of MES is a challenging, interdisciplinary process. Especially IT and production experts with different views and background have to cooperate. For successful and efficient MES software projects, misunderstandings in the specification process have to be avoided. Therefore, textual specifications need to be complemented by unambiguous graphical models, reducing the complexity by integrating interdisciplinary views and domain specific terms based on different background knowledge. Today's modeling notations focus on the detailed modeling of a certain domain specific problem area. They do not support interdisciplinary discussion adequately. To bridge this gap a novel MES Modeling Language (MES-ML) integrating all necessary views important for MES and pointing out their interdependencies has been developed. Due to its formal basis, comparable and consistent MES-models can be created for specification, standardization, testing, and documentation of MES software. In this paper, the authors present the formal basis of the modeling language and its core notation. The application of MES-ML is demonstrated taking a yogurt production as an example. Finally, the authors give some evaluation results that underline the effectiveness and efficiency of this new modeling approach with reference to four applications in industrial MES-projects in the domain of discrete and hybrid manufacturing.Comment: 10 pages, https://ieeexplore.ieee.org/abstract/document/614565

Agents enabling cyber-physical production systems

In order to be prepared for future challenges facing the industrial production domain, Cyber-Physical Production Systems (CPPS) consisting of intelligent entities which collaborate and exchange information globally are being proclaimed recently as part of Industrie 4.0. In this article the requirements of CPPS and abilities of agents as enabling technology are discussed. The applicability of agents for realizing CPPS is exemplarily shown based on three selected use cases with different requirements regarding real-time and dependability. The paper finally concludes with opportunities and open research issues that need to be faced in order to achieve agent-based CPPSs.info:eu-repo/semantics/publishedVersio

Improving transferability between different engineering stages in the development of automated material flow modules

For improving flexibility and robustness of the engineering of automated production systems (aPS) in case of extending, reducing or modifying parts, several approaches propose an encapsulation and clustering of related functions, e.g. from the electrical, mechanical or software engineering, based on a modular architecture. Considering the development of these modules, there are different stages, e.g. module planning or functional engineering, which have to be completed. A reference model that addresses the different stages for the engineering of aPS is proposed by AutomationML. Due to these different stages and the integration of several engineering disciplines, e.g. mechanical, electrical/electronic or software engineering, information not limited to one discipline are stored redundantly increasing the effort to transfer information and the risk of inconsistency. Although, data formats for the storage and exchange of plant engineering information exist, e.g. AutomationML, fixed domain specific structures and relations of the information, e.g. for automated material flow systems (aMFS), are missing. This paper presents the integration of a meta model into the development of modules for aMFS to improve the transferability and consistency of information between the different engineering stages and the increasing level of detail from the coarse-grained plant planning to the fine-grained functional engineering.Comment: 11 pages, https://ieeexplore.ieee.org/abstract/document/7499821

Summer school on intelligent agents in automation: Experience and reflections from the second edition

Several research agendas worldwide are targeting the development of Industrial Cyber-physical Systems as the next generation of intelligent embedded devices with improved interaction capabilities. These devices, and their potential uses, are though to deliver a radical increase in system sustainability, reconfigurability and flexibility which is perceived to be the root of the so called 4 th Industrial Revolution. However such technical systems, at the envisioned revolutionary scale, do not exist just yet and require a convergent and multidisciplinary research and development efforts. The academia curricula are also, albeit slowly, adjusting to the emerging education requirements. The Summer School on Intelligent Agents in Automation is a joint effort from several researchers in core areas of the 4 th Industrial Revolution landscape to close the gap and promote advanced education in this context. This paper describes the implementation of the 2 nd edition of the event as well as the experience and reflections resultant from it.info:eu-repo/semantics/publishedVersio

Summer school on intelligent agents in automation: Hands-on educational experience on deploying industrial agents

Cyber-physical systems constitutes a framework to develop intelligent, distributed, resilient, collaborative and cooperative systems, promoting the fusion of computational entities and physical devices. Agent technology plays a crucial role to develop this kind of systems by offering a decentralized, distributed, modular, robust and reconfigurable control structure. This paper describes the implementation of a summer school aiming to enhance the participants' knowledge in the field of multi-agent systems applied to industrial environments, being able to gain the necessary theoretical and practical skills to develop real industrial agent based applications. This is accomplished in an international framework where individual knowledge and experiences are shared in a complementary level.info:eu-repo/semantics/publishedVersio

Design, Application and Evaluation of a Multi Agent System in the Logistics Domain

The increasing demand for flexibility of automated production systems also affects the automated material flow systems (aMFS) they contain and demands reconfigurable systems. However, the centralized control concept usually applied in aMFS hinders an easy adaptation, as the entire control software has to be re-tested, when manually changing sub-parts of the control. As adaption and subsequent testing are a time-consuming task, concepts for splitting the control from one centralized to multiple, decentralized control nodes are required. Therefore, this paper presents a holistic agent-based control concept for aMFS, whereby the system is divided into so-called automated material flow modules (aMFM), each being controlled by a dedicated module agent. The concept allows the reconfiguration of aMFS, consisting of heterogeneous, stationary aMFM, during runtime. Furthermore, it includes aspects such as uniform agent knowledge bases through metamodel-based development, a communication ontology considering different information types and properties, strategic route optimization in decentralized control architecture and a visualization concept to make decisions of the module agents comprehensible to operators and maintenance staff. The evaluation of the concept is performed by means of material flow simulations as well as a prototypical implementation on a lab-sized demonstrator.Comment: 13 pages, https://ieeexplore.ieee.org/abstract/document/9042827

A General Methodology for Adapting Industrial HMIs to Human Operators

Modern production systems are becoming more and more complex to comply with diversified market needs, flexible production, and competitiveness. Despite technological progress, the presence of human operators is still fundamental in production plants, since they have the important role of supervising and monitoring processes, by interacting with such complex machines. The complexity of machines implies an increased complexity of human-machine interfaces (HMIs), which are the main point of contact between the operator and the machine. Thus, HMIs cannot be considered anymore an accessory to the machine and their improvement has become an important part of the design of the whole machines, to enable a nonstressful interaction and make them easy to also use less skilled operators. In this article, we present a general framework for the design of HMIs that adapt to the skills and capabilities of the operator, with the ultimate aim of enabling a smooth and efficient interaction and improving user's situation awareness. Adaptation is achieved by considering three different levels: Perception (i.e., how information is presented), cognition (i.e., what information is presented), and interaction (i.e., how interaction is enabled). For each level, general guidelines for adaptation are provided, thus defining a meta-HMI independent of the application. Finally, some examples of how the proposed adaptation patterns can be applied to the case of procedural and extraordinary maintenance tasks are presented. Note to Practitioners-This article was motivated by the problem of facilitating the interaction of human operators with human-machine interfaces (HMIs) of complex industrial systems. Standard industrial HMIs are static and do not consider the user's characteristics. As a consequence, least-skilled operators are prevented from their use and/or have poor performance. In this article, we suggest a novel methodology to the design of adaptive industrial HMIs that adapt to the skills and capabilities of operators and compensate their limitations (e.g., due to age or inexperience). In particular, we propose a methodological framework that consists of general rules to accommodate the user's characteristics. Adaptation is achieved at three different levels: Perception (i.e., how information is presented), cognition (i.e., what information is presented), and interaction (i.e., how interaction is enabled). The presented rules are independent of the target application. Nevertheless, we establish a relationship between such design rules and user's impairments and capabilities and kind of working tasks. Hence, designers of HMIs are called to instantiate them considering the specific requirements and characteristics of the users and the working tasks of the application at hand