Automated Production Systems Research Articles

Automated production of individualized products for teaching I4.0 concepts

Many trends, such as cyber-physical systems, Internet of Things or digital twins are currently predominant in research and development. However, the teaching and training of these topics is often neglected. Especially, students or participants of a training course cannot develop and apply new technologies on their own. In order to meet this demand, this paper presents an approach that segments an automated production system into modules. The complexity of the system can be varied depending on the needs of the students or participants. With this, classical automation topics as well as state-of-the-art topics can be touched and trained. Additionally, the concept is designed in such a way that it is not only applicable in university education, but also that individual topics can be taught in half-day or one-day seminars with appropriate previous experience.

An Approach to Analyze the Performance of Advanced Manufacturing Environment

The recent shift in manufacturing paradigm in terms of reconfigurable automation technologies invites the involvement of industrial mobile robots, highly automated production systems and digital information models to support manufacturing. Therefore, in the future, manufacturers need to complete automated production lines to compete in the global market. However, a current lack of performance assessment methods for the successful functioning of an advanced manufacturing line demands to describe a concept for the evaluation of such a manufacturing environment. This paper presents a concept to analyze the performance of advanced technologies integrated manufacturing line. Modeling and simulation of a case study are performed to validate and to attain the results of the proposed concept.

Self-Aware LiDAR Sensors in Autonomous Systems using a Convolutional Neural Network

Autonomous systems, as found in autonomous driving and highly automated production systems, require an increased reliability in order to achieve their high economic potential. Self-aware sensors are a key component in highly reliable autonomous systems. In this paper we highlight a proof of concept (PoC) of a deep learning method that enables a LiDAR (Light detection and ranging) sensor to detect functional impairment. More specifically, a deep convolutional neural network (CNN) is developed and trained with labelled LiDAR data in the form of point clouds to classify the degree of impairment of its functionality. The results are statistically significant and can be regarded as a general classifier for objects within LiDAR data, applied to selected cases of sensor impairment. In detecting impairment and evaluating the correctness of the captured data, the sensor gains a basic form of self-awareness. The presented methods and insights pave the way for improved safety of autonomous systems by the means of more sophisticated “self-aware” neural networks.

Design, Application, and Evaluation of a Multiagent 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.

BPMN+I to support decision making in innovation management for automated production systems including technological, multi team and organizational aspects

Abstract A joined interdisciplinary approach from systems engineering, organizational sociology and psychology is introduced using an enriched Business Process Model and Notation (BPMN+I) based modeling approach to support decision making on a management level for both mid-term decisions such as in-/outsourcing and short-term decisions such as fixing a weakness on site during start-up of a plant abroad or involving the design offices. This approach focusses on the actual collaboration between interdisciplinary teams within an organizational context by enriching BPMN with checklists applicable to all interfaces along the projects’ workflow. Our contribution aims at supporting innovation management for automated Production Systems which depends on successful interdisciplinary collaboration.

A concept for fault diagnosis combining Case-Based Reasoning with topological system models

Automated failure recovery plays an important role in improving Overall Equipment Effectiveness and is a building block of industry 4.0. However, in an increasingly dynamic market, failure recovery mechanisms need to be able to adapt to system changes. Starting with fault diagnosis in automated Production Systems for assembly and logistics, this paper proposes a novel approach to combining Model-based Reasoning on topological system models with Case-based Reasoning. The topological models are leveraged for case adaption, which significantly reduces the engineering effort of adding new fault types to the system, compared to signal-based methods. Furthermore, the approach does not rely on complete fault models existing in advance; thus, the case database can be continuously built up during operation.

Integrated production and maintenance planning for a deteriorating system under uncertain demands

To deal with today’s tough competitions, many companies have put investments into highly automated production systems with sophisticated machines. To achieve optimum performance and economic benefits, the production system is desired to operate at the maximum capacity. To keep the production process at a low cost and to satisfy customer demands, manufacturing companies have to lay appropriate production plans. In most existing studies, it is often assumed that the production process is perfect and no machine failure occurs during production planning horizon. This, however, is not the case in practice. During production many machines deteriorate due to aging or wearing, and eventually lead to failures. When a failure occurs, maintenance actions have to be performed, which decreases the capacity of the machine and disturb the initial production plan. Perturbation of production planning in an emergency situation is costly and leads to deterioration of the product quality and the service level. Therefore, it is vital to integrate the production planning and maintenance policy into a coherent strategy so as to hedge against the unexpected failures and production re-planning.In this paper, we aim to address the issue of jointly optimizing production and maintenance planning considering production capacity and service level constraint. Maintenance actions influence the production process in such a way that maintenance actions (either preventive or corrective) reduce the available production capacity in each period. Preventive maintenance is scheduled in advance and minimal repair is carried out at unexpected machine failures. We use the static-uncertainty strategy to determine the optimal cycle length of preventive maintenance and production quantity in each period, so as to minimize the expected total production and maintenance cost. Service level constraint is introduced to ensure that the customer demand in each period should be satisfied with a high probability.

Overall equipment effectiveness (OEE) evaluation for an automated ice cream production line

PurposeAs overall equipment effectiveness (OEE) is a metric to estimate equipment effectiveness of production systems, the purpose of this paper is to identify strategic management tools and techniques based on OEE assessment of the ice cream production line.Design/methodology/approachThis paper presents the collection and the analysis of data for ice cream production under real working conditions. The data cover a period of eight months. A framework process to improve the OEE of an automated production system was proposed. Six major stoppage losses, i.e. equipment failure, setup and adjustment, idling and minor stoppage, reduced speed, defects in the process, and reduced yield, were examined with the help of Pareto analysis. In addition, the actual availability (A), performance efficiency (PΕ) and quality rate (QR) measures, together with the complete OEE for each working day, week and month of the production line were shown.FindingsThe main goal of the study is to identify major stoppage losses, in order to examine and improve the overall equipment efficiency (OEE) of the ice cream production line through the application of an adequate management, i.e. TPM approach. Based on the obtained results, maintenance management strategy and production planning have been suggested to improve their maintenance procedures and the productivity as well.Originality/valueThe proposed method can be applied to each automated production system. The main benefits of this method are the improvement of productivity, quality enhancement of products, the reduction of sudden breakdowns and the cost of maintenance. Moreover, the analysis provides a useful perspective and helps managers/engineers make better decisions on the operations management of the line, and suggestions for improvement were proposed and will be implemented accordingly.

Production automation system for three-dimensional template pieces used to evaluate shell plate completeness

In the shipbuilding industry, three-dimensional (3D) templates play a key role in the completeness evaluation of shell plates with a large curvature in the shell-plate fabrication process. Currently, the information of 3D templates from a ship computer-aided design system is limited; thus, manufacturers depend on their experience to produce the templates manually. This results in the inaccuracy of templates in addition to increased production time. Therefore, if the pieces of the 3D templates can be produced automatically with accurate information, the lead time of the fabrication process can be reduced. In this study, we define a new type of template piece and develop methods for extending a boundary template and converting manufacturing information into numerical control machine input. In addition, based on the results of the study, we propose a production automation system for 3D template pieces. This system is expected to reduce the lead time of the fabrication process.

Automatic detection of electric meter position in automated assembly line turnover box

Abstract: In the process of metering and automatic production system in the measurement and verification of the loading robot, if there is a positional shift of the electric meter, the gripper of the loading robot will mechanically collide with the electric meter. Due to the large force of the loading robot, the appearance of the electric meter is damaged, and the mechanical arm of the loading robot is broken, which reduces the service life of the measuring and verifying equipment, which is not conducive to the continuous and stable operation of the automatic verification system. In this paper, an automatic detection system of electric meter position in the turnaround box is proposed, which can reduce the failure rate of the automatic verification system, improve the verification efficiency, reduce the loss of metering assets and the occurrence of safety accidents by realizing the offset detection and correction of the electric meter position in the turnover box.

Reducing the Costs of Automated Production Systems

This paper focuses on the comparison of production costs between two identical production units that are located in different countries. The trends in the field of production are dramatically changing due to the Fourth Industrial Revolution and companies have to manage production costs very thoroughly to increase their competitiveness. The aim of this paper is a cost evaluation of automated manufacturing systems, mainly considering the impact of personnel costs on costs of production. It also includes a case study with calculation performed on a full cost basis. The outcome should demonstrate the difference in production costs of before mentioned units and prove whether the personnel costs of automated production systems do have a significant impact on production costs.

In-Place Traceability for Automated Production Systems: A Survey of PLC and SysML Tools

Automated production systems are critical enablers for Industry 4.0 because these design-to-order, custom-built mechatronic systems are not only capable of delivering automation capabilities to satisfy the stakeholder requirements in the manufacturing/production domain, but doing so for a long period of time (e.g., several decades) during which numerous changing needs shall also be accounted for. Although traceability has long been recognized as key to sustain changes, little is known about how the traceability information is managed in place , i.e., in the native environments where the engineering artifacts reside. We contribute in this paper a survey of traceability support within state-of-the-practice tools: seven for programming logic controllers and six for building models in systems modeling language. We draw the similarities and differences from our survey results, and further present a design by leveraging the in-place traceability to better support the development and evolution of automated production systems.

Design of laboratories for teaching mechatronics/electrical engineering in the context of manufacturing upgrades

In the context of upgrading of the worldwide manufacturing industry, advanced automatic production systems are adopted in manufacturing enterprises moving towards intelligent manufacturing, which requires comprehensive technical abilities for mechatronic/electrical engineering professionals. This paper presents the laboratories designed for teaching mechatronics/electrical engineering in vocational engineering education, where students can develop industry-relevant skills, which adapt to the requirements of manufacturing industry upgrading. Following the analysis of the professional competence, the practical modules of the syllabus are outlined, and the corresponding labs are designed and implemented. Evaluation results indicate that the practice in the labs is helpful in improving the required technical abilities for the students.

Analysis of research in the field of automatic production systems with rigid interaggregate relation and recomposed systems

Automatic production systems with rigid inter-aggregate relation are widely used: automatic lines, etc. There are alternative solutions as flexible production systems that allow quick changeovers for the production of various applications. The main trends in systems with rigid relations and reconfigured systems with flexible relations are discussed. The main tendencies are defined. The required properties of the recomposed production systems are determined. Two main directions of development of this type of systems are revealed.

Improving the process of designing route maps in production

The paper describes the method of designing route maps, taking into account the capabilities of the production means, which will improve the efficiency of the technological processes being developed through the planning of resources. The paper presents the data used in the design of the route, as well as the model of interaction with the archive of technological processes. The basic requirements for the implementation of the proposed model at a high-tech instrument-making enterprise are described. The feasibility of using this approach in the framework of the integration of the computer-aided design system information flows for technological preparation of production and manufacturing automation systems is shown. An example of the route formation using the tools developed in the research process.

System architectures for Industrie 4.0 applications

Industrie 4.0 principles demand increasing flexibility and modularity for automated production systems. Current system architectures provide an isolated view of specific applications and use cases, but lack a global, more generic approach. Based on the specific architectures of two EU projects and one German Industrie 4.0 project, a generic system architecture is proposed. This system architecture features the strengths of the three isolated proposals, such as cross-enterprise data sharing, service orchestration, and real-time capabilities, and can be applied to a wide field of applications. Future research should be directed towards considering the applicability of the architecture to other equal applications.

Technical Debt as indicator for weaknesses in engineering of automated production systems

The concept of Technical Debt describes a situation in which a technical compromise is made despite better knowledge. The survey presented delivers insights on Technical Debt in 48 German companies supplying automated production systems. The participating companies do have some immediate benefits from taking Technical Debt under time pressure, but encounter a significant higher long-term additional effort to recover from technical debt. However, awareness for Technical Debt at these companies is low. Therefore, the automated production system manufacturers need to keep a closer eye on expenditure for Technical Debt. The developed survey can be used as a self-assessment method for other companies to compare their results with the average results from this survey.

Managing inter-model inconsistencies in model-based systems engineering: Application in automated production systems engineering

To cope with the challenge of managing the complexity of automated production systems, model-based approaches are applied increasingly. However, due to the multitude of different disciplines involved in automated production systems engineering, e.g., mechanical, electrical, and software engineering, several modeling languages are used within a project to describe the system from different perspectives. To ensure that the resulting system models are not contradictory, the necessity to continuously diagnose and handle inconsistencies within and in between models arises. This article proposes a comprehensive approach that allows stakeholders to specify, diagnose, and handle inconsistencies in model-based systems engineering. In particular, to explicitly capture the dependencies and consistency rules that must hold between the disparate engineering models, a dedicated graphical modeling language is proposed. By means of this language, stakeholders can specify, diagnose, and handle inconsistencies in the accompanying inconsistency management framework. The approach is implemented based on the Eclipse Modeling Framework (EMF) and evaluated based on a demonstrator project as well as a small user experiment. First findings indicate that the approach is expressive enough to capture typical dependencies and consistency rules in the automated production system domain and that it requires less effort compared to manually developing inter-model inconsistency management solutions.

Synthesising process controllers from formal models of transformable assembly systems

Abstract When producing complex and highly customisable products in low volumes (or in ‘batch sizes of one’), automation of production systems is critical for competitiveness and profitability in high labour-cost economies. To facilitate batch-size-of-one production, ‘topology generation’, ‘realisability’, and ‘control’ algorithms have been developed as part of the Evolvable Assembly Systems (EAS) project. The topology generation algorithm computes all the possible sequences of parallel activities that assembly resources can perform on parts and is run offline whenever the layout of the production facility changes, whereas realisability checking and controller generation are performed at run-time to check whether a production facility with a given set of assembly resources can assemble a desired product, and how the product should be assembled, e.g., which resources to use, and when. Generated controllers are output in Business to Manufacturing Markup Language (B2MML). Taken together, the algorithms thus represent a step toward a complete path from the formal specification of an assembly system and the products to be assembled, to the automated synthesis of executable process plans. This paper presents each algorithm in sufficient detail to allow their reimplementation by other researchers. Topology generation is the most expensive step in the approach. A preliminary experimental evaluation of the scalability of topology generation is presented, which suggests that, for small to medium sized production facilities, the time required for recomputing the topology is sufficiently small not to preclude frequent factory transformations, e.g., the addition of new resources.

Industry 4.0 in manual assembly processes – a concept for real time production steering and decision making

Digitalisation is continuously entering production. However, most concepts are dealing with automated production systems. The aim of this research work is to make more use of digitalisation in manual production. A real-time interface to digital planning is being developed based on different ubiquitous computing devices. An algorithm is able to answer requests and fault reports by the worker immediately. It bases on graph theory to represent the original planning data and a set of rules that allow real-time decision-making. The assembly and integration of Ariane 6 upper composite in the Ariane Group plant in Bremen is used as a case study.