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Task-Specific Decision Support Systems in Multi-Level Production Systems based on the digital shadow
(2019)
Due to the increasing spread of Information and Communication Technologies (ICT) suitable for shop floors, the production environment can more easily be digitally connected to the various decision making levels of a production system. This connectivity as well as an increasing availability of high-resolution feedback data, can be used for decision support for all levels of the company and supply chain. To enable data driven decision support, different data sources were structured and linked. The data was combined in task-specific digital shadows, selecting clustering and aggregation rules to gain information. Visual interfaces for task-specific decision support systems (DSS) were developed and evaluated positively by domain experts. The complexity of decision making on different levels was successfully reduced as an effect of the processed amounts of data. These interfaces support decision making, but can additionally be improved if DSS are extended with smart agents as proposed in the Internet of Production.
Unvorhergesehene Störungen gefährden in vielen Fällen den Kundenliefertermin. Die Produktionssteuerung hat die Aufgabe, effektiv und effizient auf diese kurzfristigen Störungen zu reagieren. Der Entscheidungsprozess beruht jedoch häufig auf einer qualitativen Analyse einer komplexen Situation anhand subjektiver Einschätzungen durch den Produktionsplaner. Zur Verbesserung der Entscheidungsfindung stellt dieser Beitrag eine App vor, die auf Basis von Echtzeitdaten und einer Simulation des Produktionssystems eine quantitative Entscheidungsfindung ermöglicht.
Ziel des Forschungsvorhabens war die Erhöhung der Effizienz und Effektivität von Suchanfragen in ERP-Systemen. Dabei sollte der Aufwand für den Nutzer reduziert und die Qualität der Ergebnisse verbessert werden. Die Erreichung der Ziele wurde durch die Entwicklung einer selbstlernenden, kontextbasierten Suchmaschine für ERP-Systeme realisiert. Mit der Berücksichtigung des Kontexts einer Suchanfrage, des Benutzerverhaltens und einer Ergebnisbewertung durch den Anwender wurde die Ergebnisqualität von Suchanfragen kontinuierlich gesteigert. Durch die Entwicklung eines Demonstrators wurde der Nutzen des Konzepts nachgewiesen, indem dieser in verschiedenen Szenarien erprobt und anhand einer Wirtschaftlichkeitsbetrachtung bewertet wurde.
Die Variantenfließfertigung ermöglicht die Herstellung konfigurierbarer Produkte bei kurzen Durchlaufzeiten und geringen Beständen. Im Vergleich zu anderen Organisationsformen der Produktion gestaltet sich die Produktionsplanung und -steuerung aufgrund der Variantenvielfalt als anspruchsvoll. Im vorliegenden Beitrag wird der erste Schritt einer Methodik vorgestellt, welche für die Konfiguration der Reihenfolgeplanung entwickelt wurde.
Mobilität in NRW neu denken
(2018)
The almost boundless possibilities of realizing saving potentials and innovations drive manufacturing companies to implement Business Analytics as part of the digitalization roadmap. The increasing research within the field of algorithm design and the wide range of user-friendly tools simplify generating first insights from data also for non-professionals. However, small and medium sized companies struggle implementing Business Analytics company-wide due to the lack of competencies. Especially the customization of a multitude of analytic methods in order to match a superordinate, business-relevant question is not done easily. This paper enables researchers as well as practitioners to close the gap between business relevant questions and algorithms. From a practical point of view, this paper helps shortening the search time for a suitable algorithm. Out of a research perspective, it aims to help positioning new algorithms within a structured framework in order to enhance the communication of algorithms’ capabilities.
Assessment of IS Integration Efforts to Implement the Internet of Production Reference Architecture
(2018)
As part of a collaborative network, manufacturing companies are required to be agile and accelerate their decision making. To do so, a high amount of data is available and needs to be utilized. To enable this from a company internal information system perspective, the Internet of Production (IoP) describes a future information system (IS) architecture. Core element of the IoP is a digital platform building the basis for a network of cognitive systems. To implement and continuously further develop the IoP, manufacturing companies need to make architecture-related decisions concerning the accessibility of data, the processing of the data as well as the visualization of the information. The goal of this research is the development of a decision-support methodology to make those decisions, taking under consideration the evaluated IS integration effort. Therefore, this paper describes the allocation of IS functions and identifies the effort drivers for the respective IS integration by analyzing the integration possibilities. Conclusively this approach will be validated in a case study.
Discrete Event Simulation (DES) is a well-known approach to simulate production environments. However it was rarely used for operative planning processes and to our knowledge never in terms of multiple disposition levels.In this paper we develop the necessary adjustments to use DES for this purpose and show some theoretical advantages.
In order to cope with the challenges of an increased demand for flexibility, quality and availability of production, maintenance measures provide a major competiveness factor for manufacturing companies. Yet, interdependencies between maintenance and production activities as well as differing target systems within the functional units of an enterprise, especially production and maintenance, raise needs for extended coordination efforts. This paper aims to develop an innovative approach for the coordination between maintenance and production activities for industrial production companies. To achieve this, the novel coordination mechanism is used. It helps to achieve maximised operational availability— for a maximised output of the production system at optimal costs. Based on the developed model, the present paper identifies findings regarding the impact of different maintenance strategies on the medium-term economic efficiency of the production system.
Today, machine manufacturers generate a significant share of their revenues with the provision of services. At the same time, they are confronted with the challenge of adopting of Industrie 4.0.
One of the most important Industrie 4.0 concepts is the idea of the digital shadow, which contributes to the comprehensive structuring of different kinds of data from different data sources. It can be defined as the sufficiently precise, digital representation of reality in real-time.
Thus, it also functions as a database of the considered area of a company that can be used for numerous applications. It serves as a central platform for the aggregation and distribution of data. Thereby, it helps to open isolated data silos. A system architecture that enables extraction of data from various sources and the aggregation of that data is an important prerequisite for the digital shadow.
In addition, the merger of data from different sources requires a model of the part of the company to be mapped digitally. In this paper, we focus on maintenance, repair and overhaul (MRO) services of machine manufacturers. The scope comprises the whole order processing of a service including the utilized resources and the obtained results.
MRO services and their single elements are mapped and structured using a case study research in a first step. Those elements provide a basis for designing the digital shadow. A second contribution of this paper is a data model for the digital shadow of MRO services that entails a comprehensive representation of that department.
The manufacturing industry has to exploit trends like “Industrie 4.0” and digitization not only to design production more efficiently, but also to create and develop new and innovative business models. New business models ensure that even SMEs are able to open up new markets and canvass new customers. This means that in order to stay competitive, SMEs must transform their existing business models.
The creation of new business models require smart products. The required data base for new business models cannot be provided by SMEs alone, whereas smart products are able to provide a foundation, given the creation of smart data and smart services they enable. These services then expand functions and functionality of smart products and define new business models.
However, the development of smart products by small and medium-sized enterprises is still lined with obstacles. Regarding the product development process the inclusion of smart products means that new and SME-unknown domains diffuse during the process. Although there are many models regarding this process there appears to be a substantial lack of taking into account the competencies enabled by the implementation of digital technologies. Hence, several SME-supporting approaches fail to address the two major challenges these enterprises are faced with. This paper generally describes valid objectives containing relevant stakeholders and their allocation to the phases of the product life cycle.
Within each objective the potential benefit for customers and producers is analyzed. The model given in this paper helps SMEs in defining the initiation of a product development project more precisely and hence also eases project scoping and targeting for the smartification of an already existing product.
Due to the drastically increasing amount of data, decision making in companies heavily relies on having the right data available. Also because of an increasing complexity of structures and processes, quick and precise flows of information become more important.
This paper introduces a new approach for modelling information flows, creating a basis for an efficient information management. It can be used to structure the information requirements and identify gaps within the information processing.
To display its benefits, the proposed Information Logistics Notation (ILN) is applied to the information logistics of todays and future energy market and grid stability management, both processes of increasing complexity.
Nowadays, the market for information and communication technologies used for IOT-applications grows daily. Since companies need technologies to transform their business processes corresponding to the digital revolution, they need to know which technologies are available, and fit the best for their use case. Their inertial issue is the lacking overview of technologies suitable to connect their production or logistics. Hence, this paper presents a methodology to select technologies (and combinations) based on their functions. It differentiates between information and communication technologies, digital technologies and connecting technologies by the physical function and its role in a cyber-physical system. Depending on the use case, the applicability of every technology varies. Due to that reason, the paper illustrates a ranked qualification of the technologies for typical use cases, focussing tracking and tracing issues in the intralogistics of producing companies. The evaluation is performed upon a literature research, a market study to identify suitable technologies, and various expert interviews to assess the applicability of the technologies.
Geschäftsmodell-Innovation
(2017)
Der Wirtschaftsstandort Deutschland ist bislang vorrangig auf die Produktion von Gütern ausgerichtet: Kraftwagen und Kraftwagenteile, Maschinen, Datenverarbeitungsgeräte sowie elektronische und optische Erzeugnisse stellten wertmäßig die Hälfte der Gesamtausfuhren des Jahres 2013 dar. Die fortschreitende Globalisierung führt zu einer verstärkten internationalen Wettbewerbsintensität bei sich schneller ändernden Produkten und einem wachsendem Differenzierungsdruck. Industrielle Dienstleistungen stellen vor diesem Hintergrund eine Möglichkeit dar, die technische Leistungsfähigkeit von Produkten zu erweitern und zeitgleich die Abgrenzung und Differenzierung von Wettbewerbern auf internationalen Märkten zu realisieren. Produkte werden durch industrielle Dienstleistungen zu umfassenden und spezifischen Lösungen erweitert, die über die Kerneigenschaften der Produkte hinausgehen und Probleme der Nutzer und Kunden als integriertes System lösen. Sach- und Dienstleistungen werden nach Belz als Leistungssysteme beschrieben, die ausgewählte Kundenprobleme nicht als einzelnes Produkt oder einzelne Dienstleistung, sondern umfassend und wirtschaftlich als Kombination aus Leistungsbestandteilen lösen.
In this paper, an approach towards energy management 4.0 will be presented. Energy management 4.0 is understood as an encompassing energy data based concept for manufacturing companies acting in an flexible energy grid of the future with the final goal of autonomous self-optimization Controlling, supervising and scheduling production and logistic steps based on a reliable communication infrastructure and real time data in accordance to achieve a maximum of profitability with regard to human factor is executed.
Guided by a four maturity levels of the "acatech Industrie 4.0 Maturity Index" developed by the German National Academy of Science and Engineering (acatech) different use cases are presented according to the steps of visibility, transparency, prognostic capacity and self-optimization. The basic idea of energy management 4.0 is described and an outlook of further steps that are needed to be evaluated for an implementation are presented.
Working capital management is one of the key disciplines that must be prudently monitored for a firm in pursuit of profits, liquidity and growth. The focus of this paper is on the engineer-to-order manufacturers, and the objective is to analyze the correlations between the reference processes of the engineer-to-order production approach with the key postulates of working-capital management and deliver a mathematical operating curves model, whose purpose and goal is basing on the rationale, that is underlying in the parent logistic operating curves theory. [https://link.springer.com/chapter/10.1007/978-3-319-66926-7_30]
Nowadays one of the most challenging tasks of producing companies is the growing complexity due to the globalization and digitalization. Especially in high wage countries, the ability to deliver fast and to a fixed date gets more and more important. To achieve this logistic target, it is necessary to optimize the Production Planning and Control (hereinafter PPC). This study investigates the effects of a change of the scheduling parameters on a target system. The focused research questions are: How can the effect of a scheduling parametersvariation on the target system of the PPC can be displayed efficiently? Is it possible to review the effect of the scheduling parameters-variation quantitatively and to derive action options?
Growing information systems (IS) often come along with growing IT complexity, because of emerging rag rug landscapes. This development causes rising IT costs and dependencies, which hinder the maintenance and expansion of the IS landscape. This article outlines the current research on published and presented methods to manage the rising IT complexity in a literature review. Because definitions of “IT complexity” vary a lot in literature, this paper also includes a definition of the term. In addition to that, it delivers a presentation of the used research methodology. Subsequently, it presents the findings in literature, highlights the research gap and – based on the literature analysis – presents, the steps that need to be taken. A discussion of the results and a summary complete the article.
Real-time data analytics methods are key elements to overcome the currently rigid planning and improve manufacturing processes by analysing historical data, detecting patterns and deriving measures to counteract the issues.
The key element to improve, assist and optimize the process flow builds a virtual representation of a product on the shop-floor - called the digital twin or digital shadow. Using the collected data requires a high data quality, therefore measures to verify the correctness of the data are needed. Based on the described issues the paper presents a real-time reference architecture for the order processing.
This reference architecture consists of different layers and integrates real-time data from different sources as well as measures to improve the data quality. Based on this reference architecture, deviations between plan data and feedback data can be measured in real-time and countermeasures to reschedule operations can be applied.
The design of data-driven industrial services in the context of industry 4.0 represents a major challenge for industrial service providers and manufacturing companies for investment goods. Data-driven services require technological and strategic components that most companies have not build up yet and that differ from current configurations. That is why many companies lack a systematic approach and implementation competence for the use of data in the context of industrial services and therefore face the challenge of not being able to expand their market position in an ever-growing competition for data.
The present paper addresses this research deficit with the aim of describing strategic features and characteristics of data-driven industrial services by identifying the related crucial features and characteristics through a morphological approach. This will enable industrial service providers to improve strategic and operative management decisions in order to define a specific strategy and to configure data-driven services.