automated Production Systems (aPS) are highly complex mechatronic systems, partly operated for several decades. Particularly in the face of ever shorter innovation cycles in the context of Industry 4.0 and intensified global competition, it is essential for aPS manufacturers to develop high-quality, maintainable, and flexibly adaptable systems. Increasing the efficiency of aPS requires the implementation of sophisticated drive concepts that meet a variety of company-and process-specific requirements. However, the evaluation of design decisions of motion concepts in aPS and the challenges faced by industrial practitioners have so far barely been addressed in research. Therefore, this paper presents the results of a field study with six companies in the aPS manufacturing sector in Germany. The results shed light on the current state of industrial practice in motion systems, the challenges that are already solved well, and the issues that still show potential for improvement and, thus, serve as an outlook for future work in motion technology.

The amount of software and its development effort in machine and plant manufacturing is continuously increasing to currently up to 35-50% of the development personnel. However, achieving mature automation software that is adaptable to changed requirements during runtime for lifetimes of several decades still poses major challenges for machine and plant manufacturing companies. Previous industrial case studies show that companies deal with these challenges with different success. However, maturity levels are still missing to categorize and compare companies' automation software and development processes and, thus, enable a cross-company benchmark. Available approaches from computer science to categorize software maturity often do not consider the characteristics of automation software or only focus on individual aspects of maturity. Thus, this paper introduces the results of a large-scale questionnaire study with 61 German machine and plant manufacturing companies to enlarge an established maturity classification with quantitative and qualitative results on success factors in the design of automation software.

automated Production Systems (aPS) are highly complex, mechatronic systems that usually have to operate reliably for many decades. Standardization and reuse of control software modules is a core prerequisite to achieve the required system quality in increasingly shorter development cycles. However, industrial case studies in aPS show that many aPS companies still struggle with strategically reusing software. This paper proposes a metric-based approach to objectively measure the m aturity of i ndustrial IEC 61131-based co ntrol s oftwar e in aPS (MICOSE4aPS) to identify potential weaknesses and quality issues hampering systematic reuse. Module developers in the machine and plant manufacturing industry can directly benefit as the metric calculation is integrated into the software engineering workflow. An in-depth industrial evaluation in a top-ranked machine manufacturing company in food packaging and an expert evaluation with different companies confirmed the benefit of efficiently managing the quality of control software.

Cyber-Physical Production Systems (CPPS) are long-living and variant-rich systems. Challenges and trends in the context of Industry 4.0 such as a high degree of customization, evolution, and different disciplines involved, e.g., mechanics, electrics/electronics and software, cause a high amount of variability. Mastering the variability of functional control software, e.g., different control variants of an actuator type, is itself a challenge in the development and reuse of CPPS software. This task becomes even more complex when considering the variability of human-machine interface (HMI) software and extra-functional software such as operating modes, diagnosis or fault handling. Moreover, the interdependencies between functional, extra-functional and HMI software pose an additional challenge for variability management and the planned reuse of these software parts. This paper illustrates the challenges in documenting the dependencies of these software parts including their variability using family models. Additionally, the current state-of-practice in industry, which was derived in questionnaires and interview studies, is shown and compared to the potential of increasing the software's reusability and thus its flexibility in the context of Industry 4.0 by concepts using the object-oriented extension of IEC 61131–3.

In the automated Production Systems (aPS) domain, companies need to continuously decrease their systems’ development times while maintaining quality to stay globally competitive. Industry 4.0 imposes additional boundary conditions, e.g., a high degree of customization, that need to be met by aPS, which frequently have to be adapted to changing requirements during their long life cycles. Since control software implements an increasing share of aPS functionality, reusing well-tested software modules can significantly contribute to saving development time and increasing its comprehensibility and maintainability. However, planned reuse of control software modules still represents a major challenge in practice, e.g., the data exchange between software modules causes dependencies, which are often not directly visible and, thus, hinder reuse. This paper presents a metric-based concept for assessing the reusability of control software modules, focusing on different implementation types of indirect data exchange. Depending on company-specific boundary conditions, the approach can be integrated at various development process steps for continuous or one-time reuse assessment. The concept has been developed and evaluated with two industrial software projects and continuous feedback from domain experts.

Automated Production Systems (aPS) are highly complex, long-living mechatronic systems, which are usually programmed according to the standard IEC 61131-3. Control soft-ware development in aPS has to cope with challenges that sharply differ from classical high-level language programming, such as the assurance of maintainability for up to five decades or hard real-time requirements, e.g., to prevent damage to humans in case of a fault. In computer science, object-oriented programming is an established means to increase software reusability and maintainability. However, this approach is seldom used in IEC 61131-3-compliant control software, although the object-oriented extension of the standard (OO-IEC) has been available since 2013. Companies using OO-IEC generally benefit from a drastic reduction in the complexity of their control software. However, certain constellations of OO-IEC elements could lead to runtime problems, which is a crucial problem regarding the hard real-time requirements of aPS to guarantee safety. Therefore, this paper introduces two metrics to detect runtime-critical control software parts and optimization potentials without executing the code or performing time measurements. Using an industrial example, the metrics are evaluated with PLC experts of two companies, who confirmed the reliability and the advantages of the metrics.

In an increasingly competitive market, short times to market and flexibility are key to success. We aim to shorten times to market by providing feasibility feedback to engineers early on in the design phase. Within the scope of this paper, we focus on intralogistics and assess feasibility based on the resources' layout and their properties. In addition to the feasibility feedback, intralogistics checks also result in potential production sequences. This additional information can be used to increase flexibility on the shop floor in case of unexpected changes during operation, e.g., a machine failing. Additionally, we provide a comparison of taxonomies of logistics resources, which we believe to be useful as a reference for the production domain.

Automated production systems (aPS) are variant-rich, design-to-order systems and an increasing proportion of their functionality is implemented by control software. In control software development, software reuse is still commonly performed via clone-and-own despite many drawbacks, e.g., copying errors. This unplanned reuse leads to a high amount of historically grown software variants, which contain valuable domain expertise. Therefore, to enable planned reuse of existing control software solutions, an analysis of legacy software, inducing documentation of identified variability, is required. While so-called Software Product Lines enable the documentation of variability, they lack suitable variability visualization tailored to the needs of aPS stakeholders such as application or module developers. To address this gap, this paper introduces a variability visualization concept tailored to the needs of aPS stakeholders with the aim of supporting them in their daily tasks. The concept was evaluated successfully within a master student's course by use of a prototypical implementation of the visualization concept.

The increasing demand for flexibility in automated production systems also affects the automated material flow systems (aMFSs) within these systems and, thus, demands reconfigurable systems. However, the centralized control concept usually applied in aMFSs hinders easy adaptation, as the entire control software has to be retested when subparts of the control are manually changed. As adaption and subsequent testing are time-consuming tasks, concepts are required for splitting the control from one centralized node to multiple, decentralized control nodes. Therefore, this article presents a holistic, agent-based control concept for aMFSs, whereby the system is divided into so-called automated material flow modules (aMFMs), each controlled by a dedicated module agent. The concept allows reconfiguring an aMFS consisting of heterogeneous, stationary aMFMs, 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 architectures, and a visualization concept to make decisions of the module agents comprehensible to operators and maintenance staff. We performed the concept evaluation using material flow simulations and a prototypical implementation on a lab-sized demonstrator. Note to Practitioners-Currently, the adaption of automated material flow systems (aMFSs) concerning their layout requires modifications to the control software, including extensive testing. This conflicts the demand for flexible and reconfigurable aMFSs due to changing requirements throughout a system's life cycle. A promising approach is the modularization of aMFSs, including their control to ease layout changes and adaptations to changing material flows (known as Plug and Produce in the scope of Industrie 4.0). However, common concerns when implementing agent-based control are the real-time capability of the controlled systems and the trust of operators in the automation regarding the safety and security of these systems. More precisely, it is feared that operators might be unable to distinguish the benevolent and malevolent behaviors of an aMFS if agents make decisions autonomously. The concept we present here addresses these issues by establishing different communication types classified according to varying real-time requirements, and by supporting operators via a human-machine interface to make agent decisions comprehensible.

The development of automated Production Systems (aPS) is an interdisciplinary process, where an increasing part of the system's functionality is realized in the respective control software. Such software projects commonly utilize programming languages standardized in IEC 61131-3. To measure, improve, and maintain source code while also promoting trust in its capabilities, an objective assessment of its characteristics is necessary. Software metrics are a means for such an evaluation. While there is an abundance of metrics available from the classical software engineering domain, these metrics focus on textual programming languages. IEC 61131-3, however, defines graphical languages, which are not targeted by renowned concepts in computer science. Besides, former research demonstrates that software engineering metrics for textual languages need adaption to be applicable in the aPS domain. Thus, this paper introduces a metrics suite consisting of adapted and newly developed measures, which focus on the graphical IEC 61131-3 language Function Block Diagram. The results are prototypically implemented in one of the leading integrated development environments for IEC 61131-3 and then evaluated regarding their understandability and applicability by practitioners at a German aPS manufacturer.

The control software of large scale industrial systems such as machines and plants in the domain of automated Production Systems (aPS) is oftentimes developed using the method clone and own. However, cloning is one of the reason for high maintenance cost in software lifecycle and thus, the need for clone detection is arising. In large scale control software, clone detection is a tedious work, which cannot be performed manually. In order to alleviate the problem of huge number of clones in control software, structural clone detection can be performed. Detecting structural clones can help in better understanding of large scale and complex software, detecting commonly-used design patterns, and software evolution. In this work, the software structure is represented as a call graph depicting software artefacts and their direct dependencies. These call graphs are compared based on graph mining approach to detect similarities between two software structures. The proposed method is adapted and applied to two industrial use cases with different size and complexity. The obtained similar fragments in the software structures are evaluated and verified through manual analysis. The results show that the proposed method is promising approach to capture the similarities between two software structures.

Industrial automated production systems are mechatronic and long living systems that undergo changing requirements throughout their life cycle. While the proportion of functionality implemented by software is growing, adjustments are usually implemented using a clone-and-own principle, which results in unmanaged software variants and versions. Furthermore, the need for adapting the control software also results from changes in other disciplines such as mechanical or electrical/electronics. The various drawbacks on software maintainability, that are provoked through clone-andown, call for a shift to modular development. As a first step to realize this migration, software projects need to be analyzed in terms of variability. Secondly, visualization patterns reflecting variability are needed to present the analysis results to domain experts. However, choosing an appropriate visualization is challenging as different domain experts pursue different aims, which should be supported by the visualization and might even require different levels of detail. In this paper, visualization patterns for three different use scenarios are proposed and evaluated using an apprentice group and industrial expert feedback.

Software product line engineering (SPLE) provides a systematic approach to manage variants and versions arising throughout the development of software systems. While SPLE is successfully applied for variant management in the domain of software engineering, the approach is still not widely spread in industrial automated production systems (aPS). Previous studies highlight the interdisciplinary nature of aPS as a reason for not applying SPLE, since control software variants and versions also result from changes in other disciplines such as the mechanical engineering department (i.e. exchange of a sensor). Additionally, the software may evolve over decades at the customer site. In order to gain a better understanding of the challenges in the development of aPS and the constraints hindering the use of SPLE, we conducted several interviews with software development engineers from the domain of aPS. The interviews main aim was to get an overview of the current state of variability management and applied planned and unplanned software reuse strategies. Based on these insights, we summarize the main results useable for a transition from currently deployed variability management concepts in aPS to the SPLE approach.

Adaptive and flexible production systems require modular, reusable software as a prerequisite for their long-term life cycle of up to 50 years. We introduce a benchmark process to measure software maturity for industrial control software of automated production systems.

A much discussed topic in the recent years is the interconnectedness of industrial plants in the field of Cyber-Physical Production Systems (CPPS). In the future, the data and aggregated information from various production plants will be available globally at any time. Particularly in maintenance, this could be a helpful information expansion for the maintenance staff, since maintenance information are not only available from one plant but also from several, similar plants. However, this information has to be presented to the worker in a suitable way, because especially in maintenance tasks, the worker often needs both hands, and his/her complete visual attention to the task. This paper presents an approach for a speech interaction system that exchanges data and information over a cloud-based system with a manufacturing plant. The worker exclusively interacts with the plant over wireless headphones and a microphone. The communication between the plant, the cloud, and the speech interaction system is described as well as use cases for maintenance and training. The approach was applied in a case study using a demonstrator plant with various use cases.

Increasing numbers of variants and versions in the domain of automated Production Systems (aPS) demand appropriate methods to handle this variability. While software product lines (SPLs), often in combination with feature modelling, are already well established in the domain of information systems, up to now SPLs are rarely used in the domain of aPS. Also, SPLs for aPS need to include variants and versions in mechanic and electric besides software leading to interdisciplinary product lines (IPLs). In this paper an existing approach of an IPL is enhanced with extended feature modelling methods and SPLs and, subsequently, applied to two industrial case studies - one in special purpose machinery and the other in plant manufacturing. Challenges for such automated Production Systems are discussed.

In the development of PLC software for automated Production Systems the method copy & paste is commonly used. However, this method leads to various disadvantages. To avoid these disadvantages, a parameter-based concept for planed reuse is presented in this paper. By means of the Siemens PLC software of an automated warehouse, the concept is defined and evaluated. In a first step, the PLC software is analyzed and reusable parts as well as variation points are identified. Subsequently, it is demonstrated that the warehouse variants can be clearly described by a suitable set of parameters. In a last step the automatic configuration of the PLC software by using the identified parameters as well as a Step7 source code template is explained and evaluated.

The specific challenges for maintenance of software and its related hardware for the domain of automated Production Systems is discussed. Presenting four industrial case studies from renowned and world market leading German machine and plant manufacturing companies, these challenges and different solution approaches are introduced with a focus on software architectures to support modularity as a basis for maintaining long-living automated Production Systems. Additionally, most critical aspects hindering classical approaches from software engineering to be successful, e.g., modes of operation and fault handling, are discussed. In the last decades, research in the field of software engineering for automated Production Systems (aPS) has been focusing on developing domain specific model-driven engineering approaches supporting the development process, but mostly neglecting the operation, maintenance and re-engineering aspects. However, the success of model-driven engineering in aPS industry has been limited because the effort to introduce model-driven engineering and to change the entire existing legacy software is estimated as too high and the benefit as too low against the background of customer specific solutions expecting a low degree of reuse.