Enhanced Planning Of Production Plants: A Case-Based Reasoning Driven Approach

Advanced industrial developments lead to increasingly customized products and shortened product life cycles. In the context of production systems, this necessitates faster engineering of suitable production resources and layouts to cope with the increasing product variety. Current engineering processes rely mainly on adapting already realized solutions and leveraging past experiences to address new project challenges. However, the knowledge about efficient planning processes is often tied to individual employees. These experiences cannot be utilized consistently, particularly in employee departure or absence due to illness. To counteract this problem, companies attempt to digitize and store knowledge in various ways. Nevertheless, the company-wide and person-independent retrieval of crucial information is still difficult or impossible. Influencing factors are, among others, non-standardized information models and forms of description. In response to these challenges, this paper introduces an approach for the standardized modeling and crosscompany provision of experiences in production plant planning. Based on the paradigms of case-based reasoning and vendor-neutral data modeling using AutomationML, a system for selecting production resources and planning related layouts is demonstrated. By determining the similarity of new product structures, whose production facilities have yet to be engineered, with products whose production facilities are already realized, suitable existing solutions regarding production resources and their placement can be submitted explicitly to a planning expert. The approach is exemplified by a scenario of engineering an assembly system for electrolysis stacks. For this purpose, the similarity determination is performed using the Hamming similarity. Thus, it can be shown that case-based reasoning, which is already successfully used in other domains, has a significant potential to accelerate the subprocesses of production plant planning

Framework For The Successful Set-up Of A Common Data Model In The Context Of An Industry 4.0-ready Plant Design Process

The production plant design process consists of a multitude of individual engineering disciplines, which rely on a variety of digital models. The individual tasks build up on each other, while each discipline consumes information from the previous processes. However, sharing relevant data across multiple companies is challenging and susceptible to miscommunication and delays. Furthermore, integrating diverse software systems, tools, and technologies create compatibility issues and hinder seamless integration. As a result, a heterogeneous, non-automated data and information landscape is created, characterized by a high level of manual data transfer. This represents a major problem on the way towards Industry 4.0. The goal of this paper is to provide a framework for the successful set-up of a common data model in the context of an Industry 4.0-ready plant design process across and along the value chain. For this purpose, a literature review of current problems in the cross-company and cross-departmental collaboration in the plant design process is provided and requirements for the framework are derived. Existing solutions and research projects are compiled and evaluated against the requirements, from which the framework's structure is concluded. The framework itself is intended to be holistic and must therefore not only include technical aspects (e.g. data interfaces, semantics), but also enable the entire organization and value chain to implement the common data model as part of the digital transformation process (e.g. employee skills, business strategy, legal conditions). Based on this, the framework is further elaborated by deducing calls for action for a successful set-up of a common data model within the research project DIAMOND (Digital plant modeling with neutral data formats). The focus should be on employees and their competencies, as these are prerequisites for shaping digital transformation. Future research must prioritize these actions to enhance technology readiness and organizational Industry 4.0 preparation

Robot speed adaption in multiple trajectory planning and integration in a simulation tool for human-robot interaction

Speed and separation monitoring (SSM) is one of the four permissible collaborative operations in human-robot interaction (HRI). At all times, it must be ensured that the speed-dependent separation distance is maintained. To guarantee this, the robot speed or the robot path can be adapted. In this paper, the robot speed adaption for multiple trajectories is implemented in an HRI simulation tool and tested in an application example. Thereby, numerous complex process situations, such as a temporary robot stop or obstacles in the collaborative workspace, can be simulated. The simulation tool enables a comprehensive simulation, analysis and optimisation of human and robot motions within the HRI, already in the planning phase

Projektatlas Kompetenz Montage : kollaborativ und wandlungsfähig

Deutschland ist im Weltmaßstab eine bedeutende Industrienation. Bei der Herstellung komplexer Industriegüter hat die Montage einen entscheidenden Anteil an der Wertschöpfung. Vor diesem Hintergrund hat das Bundesministerium für Bildung und Forschung (BMBF) im Jahr 2015 den Ideenwettbewerb „Kompetenz Montage – kollaborativ und wandlungsfähig“ ausgerufen. Wissenschaft und Praxis haben in dreijährigen gemeinsamen Forschungsund Entwicklungsaktivitäten viele neue Systemlösungen für die Montageerarbeitet. Dabei war es den 80 Projektpartnern ein besonderes Anliegen, ihre Ergebnisse direkt in der betrieblichen Praxis auf ihre Tauglichkeit zu überprüfen. Der vorliegende Projektatlas bereitet die Ergebnisse in einer neuartigen, anschaulichen Form auf. Mit dem Format des „Atlas“ wird der Versuch unternommen, alle Aspekte der Montageautomatisierung aus dem jeweiligen Blickwinkel verschiedener betrieblicher Akteure zu betrachten. Der Atlas wendet sich damit vor allem an Management, Betriebsrat, Arbeitsplanung, Arbeitssicherheitsverantwortliche, Controlling, Produktionsleitung, Personalplanung und Fachkräfte in der Montage. Damit die Gestaltung zukünftiger Montagesysteme ein Erfolg wird, sollten möglichst alle relevanten Personengruppen angemessen beteiligt werden. Wie dies gelingt, zeigen wir in den einzelnen Kapiteln des Atlas