New research paper: Integrating Real-Time Dynamic Electricity Price Forecast into Job Shop Production Scheduling Model with Multiple Machine Environments

The variability in electricity prices, driven by the intermittent nature of green energy sources, presents a unique challenge. These prices are determined using machine learning forecasting techniques based on weather and grid data. So, how can manufacturing companies enhance their sustainable production efforts by optimizing their utilization of green electricity on the shop floor?

In our latest research, featured in the ACM International Conference on Industrial Engineering and Applications 2023, we propose a mixed integer linear programming model designed for the efficient scheduling of multiple machines. This model seamlessly incorporates dynamic price forecasts, allowing manufacturers to make the most of green electricity resources.

Our research builds upon the Bachelor Thesis of Stefan Krstevski, an esteemed alumnus of Constructor University. Stefan’s dedication to mathematical modeling and data analytics for production planning and control paved the way for his academic journey, eventually leading him to the esteemed halls of the University of Cambridge. His work forms the foundation of this paper.

I also appreciate of the supports of my colleague Omid Fatahi Valilai in the publication.

#latepost #sustainableproduction #productionplanning #operationsresearch #machinelearning

The paper can be accessed here

New journal paper: ESG factors in the airline industry

How relevant environmental, social, and governance (ESG) measures for the airline industry after the COVID-19 pandemic? Which ESG indicators are the most essential for the airline industry nowadays? How important are ESG factors compared to others such as safety, destinations, and digital transformation?

Our latest paper published today in Springer Journal of Environment, Development and Sustainability tried to answer those questions using multi-criteria decision analysis (MCDA) as a subset of Operation Research (OR) that focuses on structured methods for dealing with complex decision problems.

The paper is based on the excellent Master Thesis of Alan Francisco Caraveo co-supervised by Annas Vijaya at Constructor University.

#sustainability #airlineindustry #esg #operationsresearch

It is an open access article and can be retrieved here:

Get Together and Thesis Presentations

On Thursday, May 31th, 2023, our research group organized a get-together and a series of thesis presentations. Around 16 Master and Bachelor’s students presented their thesis results on various topics. Different scientific methods were presented: systematic literature review, industrial and public survey, multicriteria decision-making, statistical analysis, explainable AI, causal machine learning, digital twin, and sustainability management. Representatives from different industry sectors, such as retail, automotive, and energy, also attended the event. On May 10th, 11 computer science students presented their results before thesis submission deadlines.

Congratulations to the students who have done excellent jobs. You can be proud of yourselves. Our research group would like to express our sincere gratitude for your contributions to our research.

Fifth Delfine consortium meeting: Integration of the ontology into the semantic middleware and presentation of the user interfaces

From March 13th to 14th, 2023, the consortium of the Delfine project met for the fifth consortium meeting at the consortium partner devolo AG in Aachen. The main topic of the event was the ontology-based Semantic Middleware and the implementation of the Delfine Green Power Index (DSI).

On the first day, the meeting was opened by Nadir Pieper from Stadtwerke Trier (SWT) with a review and the current project status as well as an outlook on the next steps. After an overview of the timing of the event, there was an overview of the project schedule and a review of completed work packages and milestones. In addition, some organizational issues were discussed with regard to the remaining project duration.

The team led by Professor Hendro Wicaksono from the Constructor University (CU) then presented the current status of their work. It started with a talk by Tina Boroukhian (CU) on the integration of the ontology into the Delfine Semantic Middleware. The innovations of the data structure and platform solution were presented. Atit Bashyal and Kritkorn Supyen (CU) then presented their results for the respective work packages. Kritkorn Supyen started with a live demonstration of the created Cypher Query Tool, which is used as a natural language interface to Semantic Middleware to query historical and forecast energy data.

Based on this, Atit Bashyal presented the current status of the forecast API for the forecast data and the underlying structure of the applications. For demonstration purposes, the Django web application was demonstrated to query the forecast data and historical data. A current paper from the Constructor University on the subject of artificial intelligence for demand response applications was then presented.

In the next presentation, Daniel Diewald from Stadtwerke Trier presented a study paper from the Trier University of Applied Sciences that was created as part of the research project on the subject of dynamic electricity prices for companies and the Delfine Green Electricity Index (DSI). In it, current electricity price models for companies were compared with the Delfine solution and transferred to the project scenario. The results showed, among other things, that the tariff models with incentive signals, such as the DSI, offer great potential for the application partners. A major obstacle is the missing roll-out of the intelligent metering infrastructure in Germany.

After a short break, the interactive part continued. There was a lively exchange on the various applications and interfaces that are made available and used in the Delfine project. Change requests, suggestions for improvement and questions were discussed and recorded among the partners.

On day 2, the event was opened by Martin Trat from the Research Center for Information Technology (FZI) with a review of day 1. Meanwhile, the consortium was able to discuss open questions from the presentation.

A live demonstration of the status of the visualization application, which was developed for users by Victor Häfner from the Karlsruhe Institute of Technology (KIT), was then presented. The users could ask questions about the application and express requests for improvement. For example, the presentation of key figures in connection with production optimization was discussed.

The next presentation was given by Mischa Ahrens (FZI) on load forecasting and MILP (Mixed Integer Linear Programming)-based production optimization. The innovations presented include an improvement in the accuracy of predictions in the production process through the use of new user training data.

Based on this, his colleague Mine Felder (FZI) presented the current status of reinforcement learning (RL). In this context, it was shown how heuristics were used as a comparison method and how the synthetic extension of the production data can be used in the RL approach.

Manuel de Melo from Pumacy presented the status of the demonstration and validation of the process data. He presented a summary of recommendations for the application partners as well as the web application with a data entry mask, which is used to validate the data. In this context, it was noted that production optimization can be improved by intervals in the seconds range.

Subsequently, Christoph Dorus from StromDAO presented the business model development that could be considered for a possible use of the DSI. For this purpose, Christoph Dorus and Thorsten Zörner (StromDAO) presented examples of current StromDAO projects in the field of dynamic electricity tariffs and their business models.

In the last lecture of the event, the carried out and upcoming dissemination activities and workshops were presented by Martin Trat (FZI). Finally, the consortium agreed on the upcoming tasks.

The next consortium meeting of the Delfine project is expected to take place in June 2023.

Research on social-cultural factors of products that influence people to shop online. A causal data analytics approach

Some eCommerce customers intend to purchase products not only because of price, quality, and environment-friendliness but also because of the social-cultural values of the products. For example, a customer wants to purchase products that can contribute to the operation of an orphanage or products that are made by a rural poor community from a certain country with a particular culture. However, since the products are purchased online, it is difficult for the customers to experience the social-cultural values of the products directly.


Please support Kaleb Kristo in conducting his research on identifying intrinsic and extrinsic factors that motivate customers to purchase such products using data analytics approach by participating in the following survey:


Research on voluntary carbon offsetting by individuals and companies

Please support Carlotta Buck in conducting her interesting research about what can lead individuals and companies perform voluntary carbon offsetting by participating in the following survey:
Carbon offsetting is an effort to compensate CO2 emission arising from industrial or other human activities through contributions to make equivalent reductions of CO2 in the atmosphere, such as clean energy, forestation, efficient cookstoves, etc.

BMW Guest Lecture

Supply chain analytics is currently a hot topic in automotive industry and an important task in production planning and control. Ishansh Gupta and Seyed Taha Raeisi gave a guest lecture session in the Bachelor’s 2nd year course “Production Planning and Control” on March 31st, 2022. The guest lecture was also attended by 3rd year bachelor students, research associates, and guests of INDEED research group.

Guest Lecture from Deloitte

On March 30, 2022, David Sanadze, an alumnus of IEM B.Sc. Class of 2018 gave an inspiring guest lecture. He shared his experience as a data analytics consultant at one of big four financial services in the world. The guest lecture gave a motivation for 2nd year Jacobs University students, who are taking the course “Data Management and Analytics in Industry 4.0”.

Joint Thesis Seminar with Telkom University Indonesia

Our group conducted a collaborative research seminar with our partner university, Telkom University Indonesia, on March 28th, 2022. In the seminar, two master’s students from the study program “Information Systems” presented their Master Theses related to the Implementation of the Internet of Things for Landslide Early Warning System and Coconut Oil Production Yields Forecast using Time Series and Regression Approaches.

Third consortium meeting of Delfine Project

The Delfine project has been running for 1.5 years. We conducted the 3rd consortium meeting on February 22nd, 2022 and discussed the progress of the last six months and defined the steps for the next six months. Some results have been achieved, such as an open access publication and three conferences. In the project, we have developed novel approaches in forecasting using different machine learning models, semantic middleware using knowledge graph, and production optimization.