2017

Welcome to IDS 2017 and Overview of Data Science Use Case Presentations Speaker: Ralf Klinkenberg, RapidMiner Download the talk: here Welcome to the first Industrial Data Science (IDS 2017) conference in the name of the whole organization team. After a short description of the state, challenges, barriers, use cases, and opportunities of Industrial Data Science and of the CRoss- Industry Standard Process for Data Mining (CRISP-DM), which is used as a redline through this event, we provide a short overview over the data science use cases presented at IDS 2017, whose presentation order reflects the steps in CRISP-DM.

Industrial Data Science - Research and Applications

in talk

September 5, 2017

Machine Learning and Data Science: Research and Applications in Industry Speaker: Prof. Dr. Katharina Morik, Head of Artificial Intelligence Unit, TU Dortmund University Download the talk: here Prof. Dr. Katharina Morik, head of the artificial intelligence group at TU Dortmund University and speaker of the collaborative research center SFB 876 on machine learning under resource constraints, provides an overview of machine learning and data science research and applications in industry.

From Industrial Engineering towards Industrial Data Science

in talk

September 5, 2017

From Industrial Engineering towards Industrial Data Science Speaker: Prof. Dr.-Ing. Jochen Deuse, Head of the Institute of Production Systems (IPS), TU Dortmund University The challenges and requirements an industrial engineer has to face in his daily busi- ness have significantly changed in the context of Industry 4.0. While the core tasks of the Industrial Engineer are rooted domain specifically in work and motion studies and work system design, his methodological spectrum is increasingly changing from using basic descriptive statistics towards digital manufacturing, factory physics, and machine learning.

From Prototype to Operative Software – Data Analytics @ Lufthansa

in talk

September 5, 2017

From Prototype to Operative Software – Data Analytics @ Lufthansa Speaker: Dr. Fabian Werner, Lufthansa Industry Solutions How do data scientists and engineers best bring their expertise into a productive state? – Lufthansa Industry solutions uses a standard approach to operationalize data analytics at organizations. We will give a general overview over analytics use cases at Lufthansa and show some practical use cases from the airline industry such as the prediction of arrival times of aircrafts or whether passengers show up in or- der to take their flight.

Holistic Development of Industrial Big-Data Applications and Services

in talk

September 5, 2017

Holistic Development of Industrial Big-Data Applications and Services Speakers: Marcel Dix and Dr. Benjamin Klöpper, ABB Download the talk: here The application of big data and data analytics for optimizing production and mainte- nance processes is one of the most important use cases for industrial IoT. The talk introduces ABB’s development process for data driven services. The development process is essentially organized in four steps: 1. Development of value propositions and deduction of relevant analytical questions 2.

Optilink – A Big Data Platform for Industrial Cloud Applications

in talk

September 5, 2017

Optilink – A Big Data Platform for Industrial Cloud Applications Speaker: Roger Feist, Achenbach Buschhütten When algorithms and solutions have been verified in laboratory environments, it’s time to pave the way for their real field application. Here Optilink® becomes a product with interesting perspectives. Starting with a bottom-up approach, Optilink® is a tool chain to acquire, transmit, and analyze huge amounts of real-time- and historical-data of machinery in a safe and scalable cloud environment.

Dynamic Bottleneck Forecasting in Flexible Manufacturing Systems

in talk

September 5, 2017

Dynamic Bottleneck Forecasting in Flexible Manufacturing Systems Speaker: Ferdinand Klenner, BMW In the context of Industry 4.0, flexible manufacturing systems are the conceptual basis for highly flexible and efficient high-volume manufacturing. But the inherent complexity of these systems and the lack of transparency impede the further increase of their efficiency. If the number of machine breakdowns exceeds the resources of operators and maintenance, it is necessary to guide the employees to the most critical machines.

Application of Data Mining for Prospective Assembly Time Determination

in talk

September 5, 2017

Application of Data Mining for Prospective Assembly Time Determination Speaker: Dr. Olga Erohin & Ralf Kretschmer, Miele When algorithms and solutions have been verified in laboratory environments, it’s time to pave the way for their real field application. Here Optilink® becomes a product with interesting perspectives. Starting with a bottom-up approach, Optilink® is a tool chain to acquire, transmit, and analyze huge amounts of real-time- and historical-data of machinery in a safe and scalable cloud environment.

Data-Mining-Based Generation of Assembly Work Plans to Accelerate Product Emergence Processes

in talk

September 5, 2017

Data-Mining-Based Generation of Assembly Work Plans to Accelerate Product Emergence Processes Speaker: Dr. Regina Wallis, Daimler The application of digital assembly planning tools leads to a large amount of data documenting product development and assembly planning results along the product emergence process. The reuse and adaptation of existing planning data can accelerate future planning processes. The presented approach uses data mining techniques to generate a suitable assembly work plan from existing planning data as a starting point for a new assembly planning task.

Prediction Model for Agile Rework Scheduling

in talk

September 5, 2017

Prediction Model for Agile Rework Scheduling Speaker: Sven Krzoska, Volkswagen (VW) Dipl.-Wirtsch.-Ing. Sven Krzoska, expert for Data Mining applications for Industrial Engineering at Volkswagen (VW AG), presents a Prediction Model for Agile Rework Scheduling and illustrates it with an example application from the automotive industry. Already today, large amounts of data are created in production environments to document the construction state and the product quality. However, in most cases, these data are not systematically analyzed and used beyond their original documentation purpose.

IDS 2017 - Welcome and Overview

Industrial Data Science - Research and Applications

From Industrial Engineering towards Industrial Data Science

From Prototype to Operative Software – Data Analytics @ Lufthansa

Holistic Development of Industrial Big-Data Applications and Services

Optilink – A Big Data Platform for Industrial Cloud Applications

Dynamic Bottleneck Forecasting in Flexible Manufacturing Systems

Application of Data Mining for Prospective Assembly Time Determination

Data-Mining-Based Generation of Assembly Work Plans to Accelerate Product Emergence Processes

Prediction Model for Agile Rework Scheduling

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