FIR e. V. an der RWTH Aachen
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5G offers the manufacturing industry a wireless, fast and secure transmission technology with high range, low latency and the ability to connect a large number of devices. Existing transmission technologies are reaching their limits due to the increasing number of networked devices and high demands on reliability, data volume, security and latency. 5G fulfills these requirements and also combines the potential and use cases of previous transmission technologies so that unwanted isolated solutions can be merged. Use cases of transmission technologies that previously required a multitude of solutions can now be realized with a single technology. However, the general literature often refers to 5G use cases that can also be realized over cables in particular. In this paper, a literature review presents the current state of research on the various 5G application scenarios in production . Furthermore, concrete characteristics of 5G use cases are identified and assigned to the identified application scenarios. The goal is to verify the identified 5G use cases and to work out their 5G relevance in order to be able to concretely differentiate them from already existing Industrie 4.0 applications.
Overview: The digital transformation of organizations continues at a frenetic pace. While some companies have achieved trailblazer status, others are finding it difficult to change and therefore are lagging. Digital leaders play a pivotal role in this transition because they can increase the confidence of their organizations behind these often risky and disruptive initiatives. In this article, we present our efforts to i) separate the practices of digitally developing and digitally mature organizations―particularly those of their leaders, ii) determine the specific trust-building actions of digitally mature leaders, iii) develop a scale to measure the human dimensions of digital leaders, and iv) discuss the future development of a reliable scale and self-assessment tool that digital leaders can use to assess their own readiness to accelerate digital initiatives.
Digital Leadership
(2020)
This article describes digital leadership-specifically character and competency-that differentiate digitally mature organizations from digitally developing organizations. We assess the differentiated actions of leaders of digitally mature organizations and discuss their results. The study is based on Patterns of Digitization survey with insights from 559 decision makers across five geographic regions-America, Europe, Asia, Africa, and Oceania designed to assess how companies are implementing digital transformation, the various strategies they employ, the investments they make, and the actions they take to achieve large-scale institutionalized digital transformations. The insights gleaned from the study should help lagging companies understand what is involved in implementing a digital transformation and what they need to do to catch up.
The research aims to get a better understanding of lean manufacturing and production management department in manufacturing industries and examine the critical success factors for effective implementation of TPM.This research will investigate critical success factors (CSFs) necessary for successful implementation of the TPM framework in manufacturing industries which help to understand how CSFs in industries have changed over time with the approaching new knowledge, globalization and what CSFs have already been measured for prior researches. To fulfill this aim and identify the direction for selecting the main critical success factors for this research, a comprehensive review of published literature has been conducted.
The outcomes of CSFs from the literature research are considered as a hypothesis. The CSF’s hypothesis authentication (accepted or rejected) for research is supported by analysis of detailed surveys from the lean experts of the manufacturing organizations.
It is necessary to believe the reality that every process in the industry impact the cus-tomers either directly or indirectly. Hence, with the world class manufacturing Indus-tries moving faster with the evolving Industry 4.0 and integrated product data man-agement methodologies, it is necessary to focus on every data attribute which con-tribute to the wholesome benefit of the business requirements especially the pro-duction processes ensuring even the internal customers to be delighted. The classi-fication of the Bill of materials with respect to the status of usage of the parts are im-portant in the automotive and other manufacturing industries because of their prime importance of making the end users confident to plan their responsible processes error-free thereby enabling a smooth and effective production processes both for new launches and for the series manufacturing of the products. Even though this classification can increase the efficiency and support for a timely build of the prod-ucts, there are also different challenges. The challenges could be the existence of the non-standardized processes, more manual approaches, varied understanding of the problems and difficulty in the integration with the existing and new Information Technology systems which keeps evolving in the automotive industry based on the increasing complexity.
This project focuses on the parts classification data attribute in the lead plants of the BMW Group, the methodology of classification of the Parts in the Bills of materials supporting the technological process partners for a smooth new vehicle Launch production which is otherwise referred to as the Preseries production. This Master Thesis aims to provide a conceptual solution proposal for the two major issues. First problem is that currently various lead plants across the BMW Group have a possibil-ity of varied processes for the Bills of materials parts classification in the entire pro-duction network. In order to be more efficient following the common best practices and processes as per the lean concept and to have an integrated and coordinated working style of all the production sites globally, there should be a standardization of the processes across the entire BMW Group. Second problem to be addressed is the methodology of Parts and Bill of Materials classification with the definition of new processes and rules for the parts classification out of the new BMW Bill of Materials Backbone system and the Bill of Materials user-interface system. In other words, al-gorithm for the future process model has to be developed in order to substitute the current conventional Parts classification data attribute in a more logical manner. This solution will have to integrate with the new world of Information Technology Systems. The following sections explain the current processes and rules of this parts classification data attribute, showing the general deficits in the current pro-cesses and how is the variation of the processes in each plants. Further sections will also explain the scientific basis for the subsequent analysis on standardization and optimization of the Parts classification in the business processes. The final sec-tion concludes with the suitable criterium and workflow model which would be pro-posed conceptually to the business processes for the possibility of substituting the current parts classification data attribute for the future systems.