Einführung einer autonomen Produktion/Introduction of autonomous production – A maturity model including recommended actions for manufacturing companies

2020 ◽  
Vol 110 (04) ◽  
pp. 177-183
Author(s):  
Elena-Clara Neumann ◽  
Simon Schumacher ◽  
Dennis Bauer ◽  
Torben Lucht ◽  
Thomas Bauernhansl ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Production Systems ◽  
Industrie 4.0 ◽  
Success Factor ◽  
Maturity Model ◽  
Manufacturing Companies ◽  
Evolutionary Path ◽  
Industrial Companies ◽  
Current State

Industrie 4.0 ist geprägt von autonomen Produktionssystemen. Das Erreichen von Autonomie stellt viele Industrieunternehmen vor große Herausforderungen. Handlungsleitende Unterstützung bei der Einführung von Autonomie ist ein essenzieller Erfolgsfaktor. Das hier vorgestellte Reifegradmodell bietet Unternehmen die Möglichkeit, den aktuellen Entwicklungsstand, die individuelle Zielsetzung und den entsprechenden evolutionären Weg dahin zu identifizieren.   The vision of industry 4.0 is characterized by autonomous production systems. Achieving this autonomy is a major challenge for many industrial companies. Supporting the implementation of autonomy is an essential success factor. The maturity model presented in this article offers an opportunity for companies to identify the current state of development, their individual objectives and the corresponding evolutionary path for implementation.

An Industry 4.0 maturity model proposal

2019 ◽  
Vol 31 (5) ◽  
pp. 1023-1043 ◽  
Author(s):  
Reginaldo Carreiro Santos ◽  
José Luís Martinho
Keyword(s):  
Literature Review ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Maturity Model ◽  
Manufacturing Companies ◽  
Content Type ◽  
Five Dimensions ◽  
Industrial Companies ◽  
Smart Products ◽  
Proposed Model

Purpose In recent years, the development and application of innovative and disruptive technologies in manufacturing environments is shaping the fourth industrial revolution, also known as Industry 4.0. The purpose of this paper is to describe a tool to assess the maturity level in implementing Industry 4.0 concepts and technologies in manufacturing companies. Design/methodology/approach Using a framework to develop maturity models found in literature, three main steps were taken: the model design from the literature review on industry 4.0 and the comparative analysis of existing models; interviews with engineers and managers of relevant industries; and pilot tests in two relevant industrial companies. Findings The proposed maturity model has 41 variables considering five dimensions (organizational strategy, structure and culture; workforce; smart factories; smart processes; smart products and services). The studied companies showed different levels of Industry 4.0 implementation. According to respondents, the model is useful in making an initial diagnosis and establishes a roadmap to proceed the implementation. Practical implications Empirical evidence supports the relevance of the proposed model and its practical usefulness. It can be used to measure the current state (initial diagnostic and monitoring assessments), and to plan the future desired state (goal), identifying which transformational capabilities should be developed. Originality/value The literature review did not return an enough complete maturity model to guide a self-administered assessment. Therefore, the proposed model is a valuable tool for companies and researchers to understand the I4.0 phenomenon, plan and monitor the transformation actions.

Konzeption digital vernetzter Produktionen*/Conception of digitally connected productions – Goal-oriented design of integrated production systems using maturity models for industry 4.0

2019 ◽  
Vol 109 (07-08) ◽  
pp. 527-530
Author(s):  
R. Ungern-Sternberg ◽  
C. Leipoldt ◽  
K. Erlach
Keyword(s):  
Industry 4.0 ◽  
Production Systems ◽  
Industrie 4.0 ◽  
Maturity Model ◽  
Wird Eine ◽  
Maturity Models ◽  
Integrated Production ◽  
System P ◽  
A Company ◽  
Oriented Approach

Technologieorientierte Ansätze bei der Konzeption von digitalisierten Produktionssystemen können zu Inkohärenzen und geringerer Effektivität des Gesamtsystems führen. Durch den hier vorgestellten zielorientierten und reifegradbasierten Ansatz wird eine Systembetrachtung ermöglicht. Das Resultat ist ein unternehmensindividuelles, abgestimmtes Konzept zur Integration von Industrie 4.0-Lösungen in ein bestehendes schlankes Produktionssystem.   Technology oriented approaches for digitalized production systems could cause incoherencies and a limited effectivity of the overall system. The presented goal-oriented approach based on a maturity model enables an overall system evaluation. Result is a company-specific, harmonized concept to integrate Industry 4.0 solutions in an existing lean production system.

scholarly journals A Maturity Level-Based Assessment Tool to Enhance the Implementation of Industry 4.0 in Small and Medium-Sized Enterprises

2020 ◽  
Vol 12 (9) ◽  
pp. 3559 ◽  
Author(s):  
Erwin Rauch ◽  
Marco Unterhofer ◽  
Rafael A. Rojas ◽  
Luca Gualtieri ◽  
Manuel Woschank ◽  
...  
Keyword(s):  
Field Study ◽  
Industry 4.0 ◽  
Assessment Tool ◽  
Assessment Model ◽  
Manufacturing Companies ◽  
Research To Practice ◽  
Maturity Level ◽  
The Past ◽  
Industrial Companies ◽  
Individual Strategy

Industry 4.0 has attracted the attention of manufacturing companies over the past ten years. Despite efforts in research and knowledge transfer from research to practice, the introduction of Industry 4.0 concepts and technologies is still a major challenge for many companies, especially small and medium-sized enterprises (SMEs). Many of these SMEs have no overview of existing Industry 4.0 concepts and technologies, how they are implemented in their own companies, and which concepts and technologies should primarily be focused on future Industry 4.0 implementation measures. The aim of this research was to develop an assessment model for SMEs that is easy to apply, provides a clear overview of existing Industry 4.0 concepts, and supports SMEs in defining their individual strategy to introduce Industry 4.0 in their firm. The maturity level-based assessment tool presented in this work includes a catalog of 42 Industry 4.0 concepts and a norm strategy based on the results of the assessment to support SMEs in introducing the most promising concepts. For testing and validation purposes, the assessment model has been applied in a field study with 17 industrial companies.

Einfluss von Industrie 4.0 auf die Fabrikplanung*/Impact of Industry 4.0 on factory planning - Effects of the special characteristics of cybertronic production systems on factory planning

2015 ◽  
Vol 105 (04) ◽  
pp. 190-194
Author(s):  
J. C. Aurich ◽  
C. Steimer ◽  
H. Meissner ◽  
N. Menck
Keyword(s):  
Industry 4.0 ◽  
Production Systems ◽  
Industrie 4.0 ◽  
Shop Floor ◽  
Factory Planning

Im Rahmen von Industrie 4.0 ergeben sich durch cybertronische Produktionssysteme (CTPS) neue Möglichkeiten in der Produktion. Dieser Fachbeitrag thematisiert die Fragestellung, wie sich neue Charakteristika zukünftiger CTPS auf deren Planung auswirken und welchen Einfluss Industrie 4.0 auf den Fabrikplanungsprozess ausübt.   In the context of Industry 4.0 (Integrated Industry), cybertronic production systems (CTPS) provide new opportunities on the shop floor. This article addresses how new characteristics of future CTPS affect the planning of these systems and how Industry 4.0 impacts factory planning.

Semantische Kommunikationsschnittstellen zur Zustandsüberwachung im Karosseriebau/Standardised I4.0 communication interfaces – Requirements and measures to establish I4.0 principles in modern production systems

2016 ◽  
Vol 106 (10) ◽  
pp. 699-704
Author(s):  
H. Fleischmann ◽  
J. Kohl ◽  
A. Blank ◽  
M. Schacht ◽  
J. Fuchs ◽  
...  
Keyword(s):  
Communication Networks ◽  
Industry 4.0 ◽  
Production Systems ◽  
Industrie 4.0 ◽  
Efficient Implementation ◽  
Smart Factory ◽  
Vehicle Body ◽  
Body Construction ◽  
Semantic Communication ◽  
Smart Factories

Industrie 4.0-Technologie verspricht Unterstützung bei der Erfüllung komplexer Produktionsaufgaben. Bisher verhindern jedoch historisch gewachsene, industrielle Kommunikationsnetze durch die oft wenig semantische, strikte Kommunikation entlang der bestehenden Ebenen der Automatisierungspyramide eine effiziente Umsetzung der Prinzipien von „Smart Factories“. Diese Veröffentlichung thematisiert die Entwicklung semantischer Kommunikationsschnittstellen am Beispiel des Karosseriebaus der Audi AG.   Industry 4.0 technology promises to support the fulfillment of complex production tasks. Even today, historically grown industrial communication networks prevent an efficient implementation of smart factory principles, especially due to a lack of semantics and the strict communication along the existing layers of the automation pyramid. This publication focuses on the development of semantic communication interfaces using the example of the digitalization of the vehicle body construction at the Audi AG.

scholarly journals Pengembangan Model Pengukuran Kesiapan Industri 4.0 Untuk Perusahaan Manufaktur di Indonesia

Jurnal PASTI ◽  
2019 ◽  
Vol 13 (2) ◽  
pp. 106
Author(s):  
Hauw Sen Rimo Tan ◽  
Aditya Andhika ◽  
Francisca Dini Ariyanti ◽  
Khristian Edi Nugroho Soebandrija
Keyword(s):  
Business Process ◽  
Industry 4.0 ◽  
Measurement Model ◽  
Transformation Process ◽  
Action Plans ◽  
Manufacturing Companies ◽  
Electronic Manufacturing ◽  
Current State ◽  
Manufacturing Company ◽  
Culture Technology

Nowadays, manufacturing companies in Indonesia are facing a great challenge in Industry 4.0 era. Manufacturing companies perceive Industry 4.0 is complex and could disturb their business process with uncertainty in results by implementing it. In other side, manufacturing companies also have difficulty in assessing their readiness to start Industry 4.0 transformation process and fail to prepare strategies and action plans clearly. This research developed a measurement model of Industry 4.0 readiness with 2 aspects, 5 dimensions and 20 variables that could be used by manufacturing companies to asses their current state. The dimensions “Awareness” and  “Leadership and Strategy” are used to measure company readiness in “Knowledge” aspect, while the dimensions “People and Culture”, “Technology” and “Operation” are used to measure company readiness in “Resources Capability” aspect. The result of the measurement categories the company in 4 level of readiness, i.e.: “Not Ready”, “Conditional Ready”, “Basic Readiness” and “Fully Ready”. This model has been tested and used to measure Industry 4.0 readiness for an electronic manufacturing company located in Jabodetabek and showed that the model is easy and practical to be used in a real manufacturing company.   Keywords: Industry 4.0, readiness measurement, readiness model, readiness index 

scholarly journals Towards a Framework for Assessing the Maturity of Manufacturing Companies in Industry 4.0 Adoption

2018 ◽  
pp. 224-254 ◽  
Author(s):  
Luca Scremin ◽  
Fabiano Armellini ◽  
Alessandro Brun ◽  
Laurence Solar-Pelletier ◽  
Catherine Beaudry
Keyword(s):  
Industry 4.0 ◽  
Industrial Revolution ◽  
Production Systems ◽  
Case Analysis ◽  
Transformation Process ◽  
Manufacturing Companies ◽  
Assessment Framework ◽  
Disruptive Technologies ◽  
Fourth Industrial Revolution ◽  
Face Complex

The recent introduction of new disruptive technologies aimed at monitoring, controlling, optimizing, and automating production systems is shifting the manufacturing landscape towards a fourth industrial revolution. In this new industrial paradigm, manufacturing companies face complex challenges requiring the development of new organizational and technological capabilities. With this context in mind, this chapter is intended to provide a maturity assessment framework to understand the transformation process in manufacturing companies transitioning to Industry 4.0. The proposed framework is applied to 10 in-depth industrial case studies in Canada and Italy, two countries with increasing awareness of the Industry 4.0 revolution. A comparative case analysis revealed four different standards, or archetypes, for Industry 4.0 adoption, which are discussed and analyzed, highlighting a relationship between a company's manufacturing configuration and its path towards Industry 4.0 adoption.

Data Analytics in der Produktionsplanung*/Data analytics for production planning

2019 ◽  
Vol 109 (04) ◽  
pp. 232-236
Author(s):  
M. Veigt ◽  
B. Staar ◽  
S. Schukraft ◽  
M. Freitag
Keyword(s):  
Production Planning ◽  
Production System ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Industrie 4.0 ◽  
Manufacturing Companies ◽  
Due Date ◽  
Factors Influencing

Durch die Digitalisierung im Kontext von Industrie 4.0 steigen die Datenmengen in produzierenden Unternehmen an. Data-Analytics-Methoden erlauben es, automatisiert Muster in diesen Daten zu erkennen, die Rückschlüsse auf die Leistungsfähigkeit des Produktionssystems geben. Der Beitrag beschreibt, wie sich Data-Analytics-Methoden nutzen lassen, um Einflussfaktoren auf die Termintreue zu identifizieren. Für die Evaluation werden die Produktionsdaten eines mittelständischen Prototypenfertigers analysiert.   With digitization in the context of industry 4.0 the data volumes in manufacturing companies are increasing. Data analytics methods allow to automatically identify patterns in these data, providing insights into the performance of the production system. This article describes how these methods can be used to identify factors influencing the due date adherence. The data of a medium-sized prototype manufacturer are used for evaluation.

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