Optimization techniques for production scheduling in the process industries
Grant agreement number: MIS 5047892 – ID 46351
Funded by Greece and the European Union (European Social Fund – ESF)
Action: Operational Programme Human Resources Development, Education and Lifelong Learning 2014-2020
Duration: 01/02/20 30/04/21

Summary

The main objective of the project is the development of new optimization-based techniques for the production scheduling problem in the process industries.
The structure of the project is based on four main phases. In the first phase novel deterministic mathematical models and solution algorithms will be developed for the optimal production scheduling of medium- to large-sized problems. Next, the issues related to the dynamic nature of all real-life problems will be tackled through the introduction of uncertainty. The incorporation of uncertainty will be realized through both the consideration of multiple discrete scenarios and the utilization of stochastic approaches. Another main objective of the project is the study of the integrated production scheduling and control problem. This will be done through the implementation of a closed-loop approach that will highlight any existing synergies between the scheduling and the control level. As a result, more efficient solutions will be extracted that will facilitate an improved decision-making process. Finally, all newly developed mathematical models and solution techniques, will be validated, through their application to real-life large-size industrial problems.
The ultimate goal is to develop optimization-based solutions for a wide-range of problems typically found in all process industries. The developed solutions will result in significant economic benefits for the industry, due to the improved production efficiency. Additionally, important environmental benefits for the society are to be expected, since the enhanced efficiency will lead to a reduction of energy waste. Finally, the proposed solutions could be the core of a computer-aided tool which will automate the procedure and provide a user-friendly interface that will facilitate the decision-making process in the process industries.
The project supports a team of two PhD candidates: George Georgiadis and Apostolos Elekidis who work jointly to achieve the objectives.
Partners: Aristotle University of Thessaloniki

Grant agreement Number: Τ6ΥΒΠ-00251
Funded by the Greek General Secretariat of Science and Technology
Action: Industrial Materials
Duration: 26/5/2020 to 25/5/2023

Summary

The main objective of this collaborative research project is the development of mathematical models, optimization frameworks and computer-aided tools for energy consumption minimization in structural ceramics production industries. Both first-principle and short-cut mathematical models will ne be developed through appropriate modeling of the ceramics drying and firing processes.

The novelty of the project lies in the fact that a wide range of the operating conditions of the drying and firing process will be studied, from the inside of the clay body to the whole kiln and dryer volumes. The new models will be validated using real experimental as well as plant data provided by KEBE and ESTIA in order to formally quantify the effect of raw material composition and key operating conditions on the final product quality and energy requirements. The validated models will provide the basis for performing advanced optimization studies in order to identify the optimal operating conditions and potential re-design options of the plant so as to reduce energy consumption while ensuring a desired product quality which is expressed by specific measures.

The ultimate aim is to develop an easy-to-use tool which will allow ceramic production industries to optimize their operation under a wide range of raw material compositions and tight design, operating and product quality constraints.

Partners:
Participant no. Participant organisation name Country
1 KEBE S.A. (Ceramics Industries of Northern Greece) Greece
2 ESTIA Consulting and Engineering, SA Greece
3. Aristotle University of Thessaloniki, Greece

Grant agreement Number: T1-05555
Funded by the Greek General Secretariat of Science and Technology
Action: Research and Innovation Activities
Duration: 1/6/2018 to 31/5/2021

Summary:

The aim of this project is to develop software tools, for the optimal design and operation of biogas plants baring the smallest environmental footprint.

The project combines experimental and simulation work, placing emphasis on the development of validated models for the digestion of substrates available in Greece.

ESTIA will perform a number of experiments using various substrates relevant to Greece and AUTH will develop the mathematical models describing the above processes.

The tools will be used for the development and parameterization of biogas plants and they will be freely available in the internet to perform
feasibility studies of biogas investments. A key activity is also the simultaneous estimation of the production, processing
requirements and environmentally safe disposal of liquid digestates as biofertilisers in an
optimized and sustainable manner. Such investments in biogas plants combine constant RES electricity
production profile with sustainable management of waste flows, being a priority according to RIS3.

Partners:

Participant no. Participant organisation name Country
1 ESTIA Consulting and Engineering, SAGR
2 Sub-contractor Aristotle University of ThessalonikiGR

Grant agreement Number: 723575
Funded by the European Commission HORIZON2020, SPIRE Programme
Action: H2020-SPIRE-2016
Duration: 1/11/2016 to 30/4/2020
Summary:
The goal of CoPro is to develop and to demonstrate methods and tools for process monitoring and optimal dynamic planning, scheduling and control of plants, industrial sites and clusters under dynamic market conditions. CoPro will provide decision support to operators and managers and develop closed-loop solutions to achieve an optimally energy and resource efficient production. In most plants of the process industries, the energy and resource efficiency of the production depends critically on discrete decisions on the use of equipment, shutdowns, product changeovers and cleaning or regeneration of equipment. CoPro will consider these discrete decisions in plant-wide dynamic optimization and develop integrated scheduling and control solutions. Advanced online data analytics will be developed for plant health and product quality monitoring. The detection of anomalies will trigger fast re-scheduling and re-optimization. CoPro will demonstrate advanced plant-wide and site-wide coordination and control in five typical use cases that cover a wide range of sectors of the process industries, and the whole value chain:
– Petrochemical production site
– Base chemicals and polymer production site
– Recycling system in cellulose production
– Consumer product formulation and packaging plant
– Food processing plant
In addition, CoPro will develop methods for the coordination of plants in industrial parks that belong to different companies, thus providing a basis for future industrial symbiosis. CoPro pays special attention to the role of operators and managers in plant-wide control solutions and to the deployment of advanced solutions in industrial sites with a heterogeneous IT environment. As the effort required for the development and maintenance of accurate plant models is the bottleneck for the development and long-term operation of advanced control and scheduling solutions, CoPro will develop methods for efficient modelling and for model quality monitoring and model adaption.
Partners:

Participant no. * Participant organisation name Country
1 (Coordinator)Technische Universitt Dortmund (TUDO)DE
2INEOS Kln GmbH (INEOS)DE
3Covestro Deutschland AG (COV)DE
4Procter & Gamble Services Company NV (P&G)BE
5Lenzing Aktiengesellschaft (LENZING)AT
6FRinsa del Noroeste S.A. (FRINSA)ES
7Universidad de Valladolid (UVA)ES
8cole Polytechnique Fderale de Lausanne (EPFL) (PAO)CH
9Ethniko Kentro Erevnas Kai Technologikis Anaptyxis (CERTH)GR
10IIM-CSICES
11LeiKon GmbHDE
12Process Systems Enterprise LTD (PSE)UK
13Divis Intelligent Solutions GmbH (divis)DE
14Argent & Waugh Ltd. (Sabisu)UK
15ASM Soft S.L (ASM)ES
16ORSOFT GmbH (ORS)DE
17Inno TSD (inno)FR

Acronym: SYmBioSys
Funded by the European Commission – HORIZON2020, Marie-Sklodowska-Curie Actions
Action: SCA-ITN-ETN
Duration: 1/9/2015 to 31/8/2019
Summary:
Mathematical, computational models are central in biomedical and biological systems engineering; models enable (i) mechanistically justifying experimental results via current knowledge and (ii) generating new testable hypotheses or novel intervention methods. SyMBioSys is a joint academic/industrial training initiative supporting the convergence of engineering, biological and computational sciences. The consortium’s mutual goal is developing a new generation of innovative and entrepreneurial early-stage researchers (ESRs) to develop and exploit cutting-edge dynamic (kinetic) mathematical models for biomedical and biotechnological applications. SyMBioSys integrates: (i) six academic beneficiaries with a strong record in biomedical and biological systems engineering research, these include four universities and two research centres; (ii) four industrial beneficiaries including key players in developing simulation software for process systems engineering, metabolic engineering and industrial biotechnology; (iii) three partner organisations from pharmaceutical, biotechnological and entrepreneurial sectors. SyMBioSys is committed to supporting the establishment of a Biological Systems Engineering research community by stimulating programme coordination via joint activities.
The main objectives of this initiative are:
Developing new algorithms and methods for reverse engineering and identifying dynamic models of biosystems and bioprocesses.
Developing new model-based optimization algorithms for exploiting dynamic models of biological systems (e.g. predicting behavior in biological networks, identifying design principles and selecting optimal treatment intervention).
Developing software tools, implementing the preceding novel algorithms, using state-of-the-art software engineering practices to ensure usability in biological systems engineering research and practice.
* Applying the new algorithms and software tools to biomedical and biological test cases.
Partners:

Participant no.*Participant organization name Country
1 (Coordinator)Imperial College London (IMPERISA)UK
2Agencia Estatal Consejo Superior de Investigaciones Científicas (CSIC)Spain
3Aristotle University of ThessalonikiGreece
4Insilico Biotechnology (INSILICO)Germany
5Process Systems Enterprise (PSE)UK
6SilicoLife (SILICOLIFE LDA)Portugal
7Humboldt-Universitat (UBER)Germany
8ProtATonce (PAO)Greece
9Rijksuniversiteit Groningen (RUG)The Netherlands
10UNIVERSITAETSKLINIKUM AACHEN (UKAACHEN)Germany
11cole Polytechnique Fédérale de Lausanne (EPFL)Switzerland

Grant agreement Number 296003
Funded by the European Commission – FP7
Web page: http://efenis.uni-pannon.hu/
Summary:
The overall objective of EFENIS is to facilitate and accelerate a move to low carbon manufacturing processes and site management by deployment and demonstration of innovative energy management systems and enabling efficiency technologies, which extend the scope of energy management outside the boundaries of a single plant to total site and then beyond the total site to district heating/cooling systems. The potential is demonstrated across a selection of the EU’s most energy-intensive sectors– thereby enabling integration across industries and processes while at the same time ensuring wide-spread deployment post-project. The EFENIS project will significantly advance the state-of-the-art with regards to site optimisation and Energy Management Systems. Currently, no deployed solution with a similar holistic scope exists. The major novelty of the project will be the creation of the foundation required for comprehensive, high-impact industrial deployment of energy systems based on Total Site Integration approach in the target industries and subsequent commercial exploitation. The project is focused on allowing integration of the developed technologies and solutions to both new designs and as retrofits to existing sites to ensure fast, widespread and cost-efficient industrial deployment. Until now, both technical and non-technical barriers have prevented the exploitation of this potential.

Partners:

Participant no.*Participant organization name Country
1 (Coordinator)Imperial College London (IMPERISA)UK
2Agencia Estatal Consejo Superior de Investigaciones Científicas (CSIC)Spain
3Aristotle University of ThessalonikiGreece
4Insilico Biotechnology (INSILICO)Germany
5Process Systems Enterprise (PSE)UK
6SilicoLife (SILICOLIFE LDA)Portugal
7Humboldt-Universitat (UBER)Germany
8ProtATonce (PAO)Greece
9Rijksuniversiteit Groningen (RUG)The Netherlands
10UNIVERSITAETSKLINIKUM AACHEN (UKAACHEN)Germany
11cole Polytechnique Fédérale de Lausanne (EPFL)Switzerland

Grant Agreement Number: PIRSES-GA-2011- 294987
Funded by the European Commision: IRSES-International Research Staff Exchange
Scheme (IRSES)
Duration: 1/6/2012 to 31/5/2016
Summary:
The main idea of the ESE proposed project is to exchange and transfer knowledge between 3 European Research groups (Imperial College – UK, University of Pannonia – Hungary and Aristotle University of Thessaloniki, Greece) and 3 distinguished and top university groups from China (Tsinghua University and Fudan University) and Korea (Yonsei University). The selected groups are leaders in the energy systems engineering field and working following different approaches and for different industrial case studies. Thus, the ESE proposed project will practically implement its programme through the following main activities: (i) Short-term secondments (2-6 months) of 86 researcher months from EU research groups and 82 researchers months from the Chinese and Korean partners (WP1). A well balanced scheme of both Early-stage (PhD students) and experienced researchers will participate in the exchanges. (ii) Short-term selected research projects covering a range of challenging energy systems engineering problems which will provide the basis for the transfer of knowledge activities (WP2) (iii) Organisation and implementation of a well-structured training programme including trainings courses, seminars, workshops and summer schools open to external and industrial participants (WP3). (iv) A well structured dissemination and exploitation plan including joint publications in peer.
reviewed international journals, joint conference presentations, presentation to the industrial partners of the consortium, and a web portal to facilitate internal communication other dissemination activities (WP4).

partners:

Participant no.* Participant organisation name Country
1Imperial College of Science Technology and MedicineUK
2University of PannoniaHungary
3Aristotle University of ThessalonikiGreece
4Tsinghua UniversityChina
5Yonsei UniversitySouth Korea
6Fudan UniversityChina

Analysis of Supply and Production Systems: an Integrated Approach
Acronym: ASPASIA
Funded by the General Secretariant of Science and Technology, Greece under the THALIS programme
Web page: http://aspasia.econ.auth.gr/
Duration: 1/3/2012 – 15/9/2015
Summary:
The design, co-ordination and management of such integrated supply networks is a difficult task due to the size of the physical network and the inherent uncertainties. Questions that need to be answered include among others:
Optimal design of supply networks: Number, size and location of the manufacturing plants, the warehouses, the distribution centers and the respective resources inside them.
Integration of financial aspects in the optimal design of supply networks.
Production decisions related to the planning and scheduling of the production plants.
Allocation of suppliers to plants, Allocation of warehouses to the markets, etc.
Inventory management and optimal replenishment policies
Procurement, production and inventory management in reverse and hybrid production systems under the uncertain condition of the returned products quality.
Transportation decisions regarding the transport mode and the capacity of the transporters.
Issues of sustainable operation of the supply networks and minimization of the environmental effects.
Development of intelligent systems and decision support systems for making operational decisions in integrated supply networks in the form of user friendly software.
This proposal makes an attempt to answer some of the above questions in order to assist the designers of multi-national companies which may be seen as integrated supply chain production-inventory-distribution networks (or simply supply networks) as well as the managers of the separate nodes/firms of these networks to answer some of the above fundamental and very practical questions. The objective of the analysis of this project is to achieve a global optimal solution to the whole supply network.
Partners:

Participant no.* Participant organisation name Country
1Aristotle University of Thessaloniki, coordinatorGreece
2University of Western MacedoniaGreece
3University of PiraeusGreece
4University of AegeanGreece

Funded by the General Secretariat of Science and Technology, Greece under the ΠΑΒΕΤ-2013 programme
Project’s code: 246-ΒΕΤ-2013
Partners:
MEVGAL Macedonian Dairy Industry S.A.
MIK-3 Integrated Information Solutions S.A.

Role of AUTH: Sub-contractor
Duration: 1/6/2014 to 31/7/2015
Summary:
The general objective of this proposal is to increase the competitiveness of: (i) dairy processing industries and (ii) software engineering companies working on the development of tools for optimal production scheduling and knowledge management in the production industries. This will be achieved by integrating knowledge management techniques with recent advances in optimal production scheduling using mathematical programming techniques. The outcome of the proposal will be a set of mathematical models, algorithms and a software tool which can be used by the dairy production industries in order to: (i) reduce total production costs by better management of the various plant resources, (ii) reduce time for the production of new products and the testing of new production recipes and (iii) improve product quality. The overall work plan relies on recent research advances in the field of food production scheduling and planning (as developed by the sub-contractor) based of mixed-integer linear programming approaches which will be integrated with efficient knowledge management techniques. It should be pointed out that the dairy processing industries are typically characterized by vast knowledge related to production recipes, different ways of operating the plant, economic, technical and market data and others. The final outcome of the project will be a systematic decision-making tool for the (i) optimal short-term production schedule of the plant, (ii) consideration of product recipe changes in the operation of the plant, (iii) the systematic consideration of various design and retrofit design options (iv) high level decisions at management level (e.g. new investments).

Partners:

Participant no.* Participant organisation name Country
1MEVGAL Macedonian Dairy Industry S.A.Greece
2MIK-3 Integrated Information Solutions S.A.Greece