SEMIT 2023 Workshops


Product as a Service (PaaS) with value retention processes

research implications for Engineering Management from introducing circular business models


         Paulina Golinska-Dawson, D.Sc. Ph.D., prof PUT

         Professor at the Poznan University of Technology (PUT),

         Institute of Logistics, J. Rychlewskiego 2 Street, 60-965 Poznan, Poland 


The circular economy (CE) concept is transforming the way in which companies design, offer, deliver their products to customers. The purpose of circular business models (CBMs) is to establish more resource-efficient approaches that allow reducing, reusing and recycling and therefore they support the transition towards a “zero waste” economy. Product as a service is a CBM in which the manufacturer (or other supply chain participant) keeps the ownership of a product and offers to customers access to its functionality  with related services for some limited period of time.  After the PaaS contract is over, the product is subject to value retention processes (reuse, repair, refurbish, or remanufacture) to make it suitable for the next use cycle. The aim of these workshops is to discuss the challenges from industrial cases, and the reflections from the ongoing international research project SCANDERE on scaling up applications of PaaS in consumer markets. The research gaps in the area of Engineering Management and the needed research directions will be discussed.


Latest Digital Transformation & Digital Technology Trends in the global business world


             Meenakshi Kaushik, professor, dean (research)

             Trinity Institute of Innovations in Professional Studies,

             Guru Gobind Singh Indraprastha University ,Delhi ,NCR, India 


Short Bio:

Dr. Meenakshi has more than 16 years of experience in teaching, training, research and corporate in the area of HR & OB, Values & Ethics, gender issues. She is also a Motivational and PDP Trainer and imparted several sessions on personality grooming in various reputed management colleges.Currently she is working as a Dean (Research) in Trinity Institute of innovations in Professional studies, GURU GOBIND SINGH INDRAPRASTHA UNIVERSITY. Her Ph.D. thesis is entitled "A Study of Leadership Effectiveness in women executives in Context of Delhi Based business organizations” has brought relevant theoretical and empirical imperatives on leadership development strategies among women leaders and executives.She has published several research papers in reputed journals SCOPUS /ABDC /UGC Care journals with several citations on Google Scholar and ResearchGate. She is also one of the editorial boards in few reputed journals UGC Care and Scopus.she is also  supervising and evaluating PhD thesis of Aligarh Muslim university (AMU, Central university) candidates and  awarded PhD degree to six AMU candidates.

She is continuously been invited as a speaker, Resource person and as a session chair in many conferences, seminars, FDPs and workshops.Recently edited & authored a book on “Digital Transformation: Recent Trends and Practices” by Himalaya Publication is available on Amazon, Kindle and Himalaya Website that is  widely appreciated and ranked globally.


The Covid-19 Pandemic, which is probably the most devastating crisis the world faced in the last many decades, had a far-reaching impact on the social and business environment.Companies had to quickly innovate to sustain and thrive in their business. It is only due to tremendous development in the digital technology world, that the companies could quickly transition to different ways of work and sustain their business.It has become very significant to introspect and examine the Digital transformation trends & practices and emerging opportunities & challenges in front of us globally. The emergence of digital transformation has made every aspect of business very simple and easy to connect with people all over the globe due to its unprecedented speed and global accessibility.The fast-paced technology is making its contribution in  every area and sphere. Digitalization refers to the use of digital technologies to bring forth change in business processes, strategies, and business models by providing new avenues and other opportunities. According to the current scenario, organizations & industries have a vision, of where exactly they want to go & seek various opportunities to digitize their organizational processes, strategies, operations & business models according to the demands of the dynamic, changing customer preferences and competitors ‘strategies & have a proper understanding of competitive landscape, long-term goals, and discovery driven planning (DDP).Organizations adopting this new business model to successfully survive in the present cut-throat competitive & digitally challenged environment to survive & they  need to adopt and follow a discovery-driven digital transformation approach by applying digital technology in the majority of their operations by becoming more customer friendly, by continuously interacting with them and their knowledge about the products and services, preferences, digitized operations and accordingly adopting the various business models. Organizations and industries shifted from physical platforms to digital platforms to fulfill their requirements and contactless, remote customer relationships, remote learning, and working from home (WFH). Organizations and industries have understood the significance of digitalization very well and have taken the initiative to undertake digital transformation to better engage and serve their people and to serve the customers’ needs to achieve competitive advantage.


Supervised machine learning using the Scikit-learn Library



LR-OASIS, National Engineering School of Tunis, University of Tunis El Manar, Tunisia

Safa Bhar LAYEB

 LR-OASIS, National Engineering School of Tunis, University of Tunis El Manar, Tunisia

Short Bio

Marwa HASNI is Assistant professor in Industrial Engineering at ISSIG Gabes – University of Gabes. She holds a PhD in Industrial Engineering from National Engineering School of Tunis - University of Tunis El Manar and member of the Laboratory OASIS, National Engineering School of Tunis, University of Tunis El Manar, Tunisia since 2016. She also holds a diploma of Engineer in Industrial Engineering and Logistics of the National Engineering School of Carthage-University of Carthage.Her research focuses on the development and the analysis of forecasting techniques applied to production systems and to financial and banking systems. Theinterest being non-parametric sampling techniques and those associated with the Machine learning and deep learning approaches. Marwa HASNI has published and reviewed a number of research studies on the side of several international journals namely: International Journal ofProduction Economics, International Journal of Production Research, International Journal ofDecision Sciences, Risk and Management, Managerial and Decision Economics, International Journal of Economics, and Strategic Management of Business Processes.

Safa Bhar Layeb is currently a professor of industrial engineering and an active member of the OASIS Laboratory at the National Engineering School of Tunis, Tunisia. Safa holds a Polytechnic Engineering degree, a Master's degree in Mathematical Engineering, a Ph.D. in Applied Mathematics, and a university habilitation (HDR) in Industrial Engineering. She is the founding chair of the African Working Group in Health Systems and member of the Executive committee of the African Federation of Operations Research Societies (AFROS). She has served as guest editor and reviewer for over twenty international journals (ANOR, CAIE, RAIRO,…). She is an active member of the editorial, organizing and scientific committees of several international conferences. She has supervised over twenty Master and Ph.D. thesis in collaboration with international institutes (Politecnico di Milano, Italy; Université de Moncton, Canada; Faculty of Transportation Engineering and Vehicle Engineering, Hongrie; Université de Tlemcen , Algérie; etc.). She has co-authored over thirty papers in reputable indexed journals, fifty papers in international conferences and, twenty chapter books. Her teaching and research interests include Operations research, optimization and data science based-approaches and their applications in healthcare organizations, industrial engineering, logistics, and supply chain management.


In this workshop, we will dive into the fascinating world of machine learning using the powerful Scikit-learn library. Whether you are new to the field or looking to expand your knowledge, this hands-on session will provide you with the essential skills to build and deploy machine learning models.  We will start by introducing the concept of supervised learning and exploring various training techniques, including the popular Train-test-Split method. You will learn how to optimize your models using cross-validation, validation curves, and GridSearch CV, ensuring the best performance for your data. Data preprocessing plays a crucial role in creating accurate models, and we'll cover various techniques to clean and transform datasets, including using the "impute" module for handling missing data. Additionally, we will delve into variable selection techniques, allowing you to identify the most relevant features for your models and enhance their performance.

The main goal of the workshop is to develop a pipeline for heterogeneous dataset processing and apply a machine learning-based analysis using the Scikit-learn Library. The schedule will be as follows:


Estimated duration

Supervised and Unsupervised machine learning model


Training technique: Train-test-Split
Optimization techniques: Cross-validation, Validation curve, GridSearch CV, learning curves
Validation: Regression/Classification metrics


Data pre-processing techniques: Variable selection techniques/data scaling techniques
Impute module for data cleaning
Put it all together to conduct a simple ML project




Fitting Hierarchical Structural Equation Models using h-likelihood Approach


Rezzy Eko Caraka

           Researcher, National Research and Innovation Agency (BRIN), Indonesia

SRF, Ulsan National Institute of Science and Technology (UNIST), South Korea

Visiting Professor, Pukyong National University (PKNU), South Korea


We present hsem R package for fitting structural equation models using the hierarchical likelihood method. This package allows extended structural equation model, including dynamic structural equation model. We illustrate the use of our packages with well-known data sets. Therefore, this package are able to handle two serious problems inadmissible solution and factor indeterminacy.


“Dissemination of Digital Youth Life Health Platform(DYL-HP)”

project supported by the European Union(EU)



       Prof. Dr. Servet SOYGÜDER,

       Ankara Yıldırım Beyazıt University, Faculty of Engineering and Natural Sciences, Department of Industrial Engineering

Short Bio

Servet SOYGUDER received the B.Sc. degree in 2001 from Mechanical Engineering, M.Sc. degree in 2004 from Mechanical Engineering at Firat University and Ph.D. degree in 2009 from Mechanical Engineering at Firat University, Elazig, Turkey. His current research interests are Robot Control, Legged Robot Control, Pronking Robot Control, Intelligent Control, PLC Control, Mechatronic, Industrial Applications, Mechanism Design, Machine Theory and Dynamic and PLC Control. He took first prize from III. and IV. International Convention Competition in 2008-2009 years. He did the first Post Doctoral in department of Computer Engineering at Tennessee State University, Intelligent Robot Control Laboratory, Nashville, USA in 2010. He worked as Associate Professor Dr. at Firat University between 2010 and 2015. He has done the second Post Doctoral and given Robotics and Kinematics and Dynamics of Machinery lectures at department of Engineering Technology at Middle Tennessee State University, Merfreesboro, USA in 2015-2016. Also, He worked as an Adjunct Faculty Professor at department of Mechanical Engineering at Tennessee State University between 2016-2018. Now, Prof. Servet Soygüder is a full time Professor at the Department of Industrial Engineering, School of Engineering and Science, Ankara Yıldırım Beyazıt University (AYBU), Turkey. His general interests include robotics, system dynamics and control, advanced control theory, mechanism design, intelligent control, operations research, and mechatronics. Also, Dr. Soygüder’s special research interests are biomedical robotics and autonomous mobile robots. He is the coordinator of the project named "Digital Youth Life Health Platform (D-HP)" supported by the EU.


DYL-HP is a digital platform and a mobile application that offer health and sports services live and free of charge, with the awareness of healthy young life that all humanity needs during and after the Covid-19 pandemic, as an alternative to established physical hospitals. Digital Youth Life Health Platform(DYL-HP) is one of the most comprehensive projects of Ankara Yıldırım Beyazıt University(AYBU), supported by the European Union(EU) as project 2021-2-TR01-KA220-YOU-000049540 and the project coordinator is Prof. Dr. Servet SOYGÜDER.