Analytics

Analysis of Resilience in Logistics

Analysis of Resilience in Logistics

Best-practice approaches of selected players
Boris Zimmermann, Philipp Knauf
The paper analyzes the improvement of resilience in logistics in contrast to lean management. First, possible success factors of resilience will be identified, including agility, redundancy in the form of capacity reserves, process transparency, management of personnel and risk, supply chain management and the formation of liquidity reserves. Eight face-to-face interviews with leading logistics companies will be conducted to examine these success factors. The aim is to identify best practice approaches for improving resilience and to examine possible conflicts of objectives with lean management.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 4 | Pages 50-54 | DOI 10.30844/IM_23-4_50-54
Life Cycle Assessments at Aircraft Manufacturers

Life Cycle Assessments at Aircraft Manufacturers

An analytical decision model for assessing the potentials
Dennis Keiser, Birte Pupkes, Jonas Wagner, Michael Freitag ORCID Icon, Rafael Mortensen Ernits, Matthias Reiß, Axel Becker
The aviation industry faces significant challenges in reducing the environmental impact of global air traffic. This results in the goal of net zero emissions by 2050. Innovations and new technologies must be implemented along the entire value chain to achieve this goal. In this context, investments and decisions have to be evaluated based on their potential to reduce environmental impacts. One method for operationalizing these issues is the life cycle assessment framework. This paper presents an analytical decision model for the potential assessment of LCA at aircraft manufacturers. The basis of the model is the derivation of criteria for the assessment and the identification of use cases along the value creation process. Based on the decision model, first concrete application scenarios are identified. (Only in German)
Industrie 4.0 Management | Volume 39 | 2023 | Edition 3 | Pages 62-66
On-Site BLE-Based Data Collection

On-Site BLE-Based Data Collection

Hendrik Jonitz, Thomas Braml, Eva-Maria Kern, Marius Herzog
The increasing industrialization of the construction industry enables the implementation of a standardized process performance management, which can be used to analyze and control operational processes on construction sites [1]. This requires appropriate process data. The subject of this paper is the presentation of a structured procedure for process data collection based on Bluetooth Low Energy. The experiences gained in the course of field studies are used to derive opportunities and challenges and thus provide practical information on the use of BLE for process data collection. (Only in German)
Industrie 4.0 Management | Volume 39 | 2023 | Edition 3 | Pages 42-47
Methods for Designing Enterprise Architecture in Manufacturing Companies

Methods for Designing Enterprise Architecture in Manufacturing Companies

EAM as enabler for the design of transferable AI solutions
Arno Kühn, Arthur Wegel ORCID Icon, Jonas Cieply ORCID Icon
A study by the German Academy of Science and Engineering (acatech) indicates that artificial intelligence (AI) is of growing importance for the success of manufacturing companies [1]. The emerging, data-driven solutions in the manufacturing field are highly diverse, both in terms of the processes and the locations (different factories, factory sub-areas, etc.) where these solutions are implemented. Often the solutions are also hardly scaled beyond the limits defined in the pilot project. When such an AI project ends, the goals of a use case are fulfilled, but this often results in another isolated solution being added to the company’s established IT system landscape. The data this solution delivers is not further used, and complex maintenance requirements negate any gains in efficiency.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 1 | Pages 37-42 | DOI 10.30844/I4SE.23.1.106
COVID-19: A Catalyst for Digitalization and Transparency?

COVID-19: A Catalyst for Digitalization and Transparency?

A study on the effects of the pandemic
Johannes Schnelle ORCID Icon, Henning Schöpper ORCID Icon, Wolfgang Kersten ORCID Icon
The COVID-19 crisis had an unmistakable impact on the procurement situation in global supply chains, to which companies had to adapt quickly. The effects make it clear that to reduce risks, companies must address the structure and transparency of supply chains. The following article examines what knowledge the actors have and how digitalization can lead to further improvement. The results show that companies currently have little supply chain knowledge beyond their direct suppliers, but are increasingly able to obtain the supply chain data they require. At the same time, the results indicate that there is still potential to increase transparency and the use of data.
Industrie 4.0 Management | Volume 37 | 2023 | Edition 1 | Pages 27-31 | DOI 10.30844/I4SE.23.1.72
Data as Basis for Business Models

Data as Basis for Business Models

Recommendations for Competitive Predictive Maintenance Business Models
Sven Seidenstricker, Saskia Ramm, Barbara Dinter
The combination of product service systems and big data requires a change in the existing, traditional business models and a repositioning of the companies. Since these changes are often a challenge, this article uses the example of predictive maintenance to present the influences of big data and product service systems on the business models of medium-sized companies in mechanical and plant engineering. Based on a systematic literature review in combination with expert interviews, numerous practical business model implications were obtained, providing sound guidance for industry representatives.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 6 | Pages 33-36 | DOI 10.30844/IM_22-6_33-36
Demand Planning Falcon

Demand Planning Falcon

Precise stochastic demand calculation with a newly developed digital planning method
Alexander Schmid, Thomas Sobottka, Samuel Luthe, Wilfried Sihn
Precise stochastic demand calculation is the key to successful material planning, i. e. to always have exactly the right quantity on hand. However, decision-makers are faced with the dilemma of which of the many forecasting methods they should use, adapted to the item properties as much as possible. This paper examines the optimization potential of a self-developed automatically optimizing forecasting approach based on ten common forecasting methods, which are evaluated using two case studies from the capital goods industry.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 6 | Pages 47-50 | DOI 10.30844/IM_22-6_47-50
DataLab WestSax – R&D Setting for Regional Data-based Value Creation Experiments

DataLab WestSax - R&D Setting for Regional Data-based Value Creation Experiments

Ein regionaler Katalysator für datenbasierte Wertschöpfungsprozesse
Christian Leyh, Wibke Kusturica ORCID Icon, Sarah Neuschl, Christoph Laroque ORCID Icon
New types of value creation characterized by extensive data use and cross-company data sharing are becoming increasingly important for companies. However, many barriers slow down the path towards data-based value creation, especially for SMEs. Companies often lack specific ideas for data usage or digitalization and data competencies. As a result, there is often untapped value creation potential in companies. By describing a real laboratory setting with real experiments, this article demonstrates support options for companies to identify their own "data treasure" and to lift it.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 6 | Pages 37-41 | DOI 10.30844/IM_22-6_37-41
Automated Environment Analysis – Generation of AI Training Data Sets

Automated Environment Analysis - Generation of AI Training Data Sets

Annika Lange ORCID Icon, Julia-Anne Scholz, Thomas Knothe ORCID Icon, Magdalena Scharf
To show SMEs a way to identify changes at an early stage, the interactive situation awareness monitor developed by Fraunhofer IPK is used. This gives companies an individually structured overview about their environment and their company (e. g. order situation). The area of the corporate environment is currently being expanded to include the compa- ny-specific component of automatic recognition of context-related data in order to provide relevant information to a company automatically. For this purpose, a machine learning model is developed and trained using company-specific data sets. First- ly, it is necessary to create the data sets with relevant and irrelevant environment information. For that, the PESTEL analysis is applied in this paper. Further- more, advantages and disadvantages of the analy- sis for generating data sets are discussed.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 4 | Pages 19-22
Digitally Networked Business Models

Digitally Networked Business Models

Structured Benefit and Effort Estimation for Digital and Hybrid Business Model Innovation
Sebastian Beiner, Steffen Kinkel ORCID Icon, Dennis Richter
An essential component of digital value creation is the innovation of digitally networked business models. By networking different actors and service bundles, new customer value can be created. However, this networking leads to increased complexity, which makes it difficult for tradition- al industrial companies in particular to exploit these opportunities in a meaningful way. For this reason, a system is presented that reduces com- plexity through modelling and makes it possible to compare the effort and benefits of business model ideas at an early stage.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 4 | Pages 28-32
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