Marcel Ph. Mayer

Self-optimising Production Systems

One of the central success factors for production in high-wage countries is the solution of the conflict that can be described with the term “planning efficiency”. Planning efficiency describes the relationship between the expenditure of planning and the profit generated by these expenditures. From the viewpoint of a successful business management, the challenge is to dynamically find the optimum between detailed planning and the immediate arrangement of the value stream. Planning-oriented approaches try to model the production system with as many of its characteristics and parameters as possible in order to avoid uncertainties and to allow rational decisions based on these models. The success of a planning-oriented approach depends on the transparency of business and production processes and on the quality of the applied models. Even though planning-oriented approaches are supported by a multitude of systems in industrial practice, an effective realisation is very intricate, so these models with their inherent structures tend to be matched to a current stationary condition of an enterprise. Every change within this enterprise, whether inherently structural or driven by altered input parameters, thus requires continuous updating and adjustment. This process is very cost-intensive and time-consuming; a direct transfer onto other enterprises or even other processes within the same enterprise is often impossible. This is also a result of the fact that planning usually occurs a priori and not in real-time. Therefore it is hard for completely planning-oriented systems to react to spontaneous deviations because the knowledge about those naturally only comes a posteriori.

Automation of robotic assembly processes on the basis of an architecture of human cognition

A novel concept to cognitive automation of robotic assembly processes is introduced. An experimental assembly cell with two robots was designed to verify and validate the concept. The cell’s numerical control—termed a cognitive control unit (CCU)—is able to simulate human information processing at a rule-based level of cognitive control. To enable the CCU to work on a large range of assembly tasks expected of a human operator, the cognitive architecture SOAR is used. On the basis of a self-developed set of production rules within the knowledge base, the CCU can plan assembly processes autonomously and react to ad-hoc changes in assembly sequences effectively. Extensive simulation studies have shown that cognitive automation based on SOAR is especially suitable for random parts supply, which reduces planning effort in logistics. Conversely, a disproportional increase in processing time was observed for deterministic parts supply, especially for assemblies containing large numbers of identical parts.

Considering ergonomic aspects of head-mounted displays for applications in industrial manufacturing

In this paper, we apply a comprehensive approach to evaluate and analyze potential physiological and subjective workload effects of the application of head-mounted displays (HMDs) during a typical 3.5 hrs assembly operation. The approach refers to physical as well as cognitive workload associated with HMDs. The methods for capturing and determining physiological workload include an analysis of visual acuity, of visual field, electromyography (EMG), and general posture analysis (OWAS). Subjective ratings for overall workload (BLV, RSME) and simulator sickness (SSQ) are considered and analyzed in order to complete the analysis. Their feasibility and practical implementations are discussed based on the results of a pre-test with a smaller sample size in order to give recommendations for their practical use during on-going experiments and for future industrial applications.

Design and Implementation of a Cognitive Simulation Model for Robotic Assembly Cells

Against the background of a changing global economy, new production technologies have to be developed to stay competitive in high-wage countries. Therefore, an integrated cognitive simulation model (CSM) has been developed to support the human operator and the assembly process. By making the behavior of the system more intuitive the cognitive compatibility between the operator and the production system is enhanced significantly. The presented CSM faces three different challenges: (1) visualizing the behavior of the system to give the human operator an understanding of the technical systems, (2) cognitive control of a real robotic assembly cell and (3) performing mass simulations in order to evaluate parameters, new assembly or planning strategies or the assembly of new products. Additionally, a graph-based planner supports the cognitive planning instance for realizing complex tasks.

A graph based hybrid approach of offline pre-planning and online re-planning for efficient assembly under realtime constraints

Assembly tasks, e.g. the assembly of an automobile headlight, are a big challenge for nowadays planning systems. Depending on the problem domain, a planner has to deal with a huge number of objects which can be combined in several ways. Uncertainty about the outcome of actions and the availability of parts to be assembled even worsens the problem. As a result, classic approaches have shown to be of little use for reactive (online) planning during assembly, due to the huge computational complexity. The approach proposed in this paper bypasses this problem by calculating the complex planning problems, e.g. which parts must be mounted in which sequence, prior to the actual assembly. During assembly the precalculated solutions are then used to provide fast decisions allowing an efficient execution of the assembly. Within this paper this online planning combined with offline planning and the assessment of realtime constraints during assembly could be executed in the future will be described.

Requirements for Modeling the Human Operator in Socio-Technical Production Systems

The changing world economy makes high demands on todays production systems. In order to stay competitive, companies, especially in high-wage countries, have to adjust their production for enabling customer individual wishes. The human operator provides meaningful skills including sensorimotorical skills and the capability of creative thinking from which the production system can significantly benefit. For establishing effective human-machine cooperation, both the employee and the technical system need to have an understanding of each other so that they can estimate the counterpart. In this paper, the requirements for introducing the human operator in technical models of production systems are described. Furthermore, first solutions are presented to implement effective human-machine cooperation.

Using anthropomorphism to improve the human-machine interaction in industrial environments (part II)

The idea of socio-technical systems emphasizes the mutual interrelationship between humans and technical system considering the human operator as an integral part of the system. However, to use the full potential of this idea the technical system has to be perceived and accepted as a team-partner. Anthropomorphism is a promising approach to improve the acceptance of non-human entities as team-partners. In the second part of this joint contribution we present a revised experimental setup of the studies presented in the first part. A virtual environment consisting of a robotized assembly cell was utilized to conduct a prediction experiment with nine subjects comparing anthropomorphic and robotic speed profiles on a gantry robot. As in the first part the task of the participants was to predict the target position during movement. The results show significant effects towards shorter prediction time and less errors when using anthropomorphic speed profiles.

3D Assembly Group Analysis for Cognitive Automation

A concept that allows the cognitive automation of robotic assembly processes is introduced. An assembly cell comprised of two robots was designed to verify the concept. For the purpose of validation a customer-defined part group consisting of Hubelino bricks is assembled. One of the key aspects for this process is the verification of the assembly group. Hence a software component was designed that utilizes the Microsoft Kinect to perceive both depth and color data in the assembly area. This information is used to determine the current state of the assembly group and is compared to a CAD model for validation purposes. In order to efficiently resolve erroneous situations, the results are interactively accessible to a human expert. The implications for an industrial application are demonstrated by transferring the developed concepts to an assembly scenario for switch-cabinet systems.

Artificial cognition in autonomous assembly planning systems

Cognition is of great interest in several scientific disciplines. The issue is to transfer human cognitive capabilities to technical systems and so generate artificial cognition. But while robots are learning to communicate or behave socially only a few examples for applications in production engineering and especially in assembly planning exist. In this field cognitive systems can achieve a technological advance by means of self-optimization and the associated autonomous adaption of the systems behavior to external goal states. In this paper cognitive technical systems and their software architectures in general are discussed as well as several assembly planning systems. A precise autonomous assembly planning system and its implementation of cognitive capabilities is presented in detail.

Cognitive Engineering for Direct Human-Robot Cooperation in Self-optimizing Assembly Cells

In a work system with direct human robot cooperation the conformity of the operators expectation with the behavior of the robotic device is of great importance. In this contribution a novel approach for the numerical control of such a system based on human cognition and a cognitive engineered approach for the encoding of the systems a priori knowledge is introduced. The implementation using an established method in the field of design of cognitive systems is compared to a schema describing human decision making. Finally, simulation results of the implementation are compared to empirical tests with individuals.