IN4PL 2021 Abstracts

Area 1 - Industry 4.0
Full Papers Short Papers
Area 2 - Intelligent Manufacturing and Management
Short Papers
Area 3 - Logistics and Operations Research
Full Papers Short Papers

Area 1 - Industry 4.0

Full Papers
Paper Nr: 7
Title:

Characterizing N-Dimension Data Clusters: A Density-based Metric for Compactness and Homogeneity Evaluation
Authors:

Dylan Molinié and Kurosh Madani
Abstract: The new challenges Science is facing nowadays are legion; they mostly focus on high level technology, and more specifically Robotics, Internet of Things, Smart Automation (cities, houses, plants, buildings, etc.), and more recently Cyber-Physical Systems and Industry 4.0. For a long time, cognitive systems have been seen as a mere dream only worth of Science Fiction. Even though there is much to be done, the researches and progress made in Artificial Intelligence have let cognition-based systems make a great leap forward, which is now an actual great area of interest for many scientists and industrialists. Nonetheless, there are two main obstacles to system’s smartness: computational limitations and the infinite number of states to define; Machine Learning-based algorithms are perfectly suitable to Cognition and Automation, for they allow an automatic – and accurate – identification of the systems, usable as knowledge for later regulation. In this paper, we discuss the benefits of Machine Learning, and we present some new avenues of reflection for automatic behavior correctness identification through space partitioning, and density conceptualization and computation.
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Short Papers
Paper Nr: 19
Title:

Adopting Artificial Intelligence in Danish SMEs: Barriers to Become a Data Driven Company, Its Solutions and Benefits
Authors:

Nadeem Iftikhar and Finn E. Nordbjerg
Abstract: Artificial intelligence allows small and medium-sized enterprises (SMEs) in the manufacturing sector to improve performance, reduce downtime and increase productivity. SMEs in Denmark are still struggling to implement artificial intelligence based strategies since they face a range of challenges, such as business applications, data availability, organizational culture towards the acceptance of new technologies, investment in new technologies, skills gap, development process and effective strategy. In the beginning, the paper describes the challenges faced by SMEs in adopting artificial intelligence. Then, the paper suggests solutions to overcome these challenges and discusses the importance of artificial intelligence as well as the opportunities it offers to SMEs.
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Paper Nr: 20
Title:

Human Digital Twin in Industry 4.0: Concept and Preliminary Model
Authors:

Yannick Naudet, Alexandre Baudet and Margot Risse
Abstract: Digital Twins originally concern technical systems and do not yet integrate human elements properly. This limits their quality and usefulness when we consider systems where machines and human workers still cohabit. This paper presents the concept of Human Digital Twin (HDT), the human equivalent of a Digital Twin (DT), which aim at being coupled with DTs of technical elements in systems where humans play a role. We detail the state of the art on the subject, propose a definition for HDT and a preliminary human model, bringing foundations for handling the human factor in industry with digital twins.
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Paper Nr: 22
Title:

Design and Deployment of Digital Twins for Programmable Logic Controllers in Existing Plants
Authors:

Stephan Schäfer, Dirk Schöttke, Thomas Kämpfe, Kiril Ralinovski, Bernd Tauber and Ralf Lehmann
Abstract: Digitization and network integration of production environments are two core prerequisites for changeable production environments according to a digital factory. In addition, consistent and cross-system descriptions of the equipment and abilities are required over the entire life cycle of plants. This descriptions can be done with Asset Administration Shells, which are a useful tool for the design of new facilities and their system components. Currently, industrial plants usually use programmable logic controllers, which are programmed with domain-specific programming languages. The use of these programming languages leads to an inflexible coupling of programmable logic controllers and their sensors and actuators with the process. If the plant configuration is changed later, a new engineering process with extensive reprogramming is required. However, in many cases, clarity and completeness of changes are not sufficiently addressed in the accompanying documentation. The paper discusses the results of the project ”OpenBasys 4.0”. A project goal is to retrofit a conventional existing plant with programmable logic controllers into a reconfigurable plant design by using the BaSys 4 middleware. A method was developed and exemplarily implemented on a prototype. The focus of the method is on the automated generation of Asset Administration Shells and their use.
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Paper Nr: 23
Title:

Reconfigurable Scheduling as a Discrete-Event Process: Monte Carlo Tree Search in Industrial Manufacturing
Authors:

T. J. Helliwell, B. Morgan, A. Vincent, G. Forgeoux and M. Mahfouf
Abstract: In this paper we introduce a theoretical basis for reconfigurable makespan scheduling that is computationally-efficient and general purpose in manufacturing. A full-scale scale case study for batch production in the aerospace industry is shown. A knowledge-based Discrete-Event System, based on a Timed Petri Net, is injected with the initial - current - state and simulated to generate trajectories that represent valid possible schedules or policies analogous to the Monte-Carlo Tree Search (MCTS) planning algorithm. A new, concise, evolutionary metaheuristic is proposed called Elitist Trajectory Mutation (ETM) in order to exploit high performing schedules in localising search and optimisation. The advantage of this approach is reconfigurability, extensibility and ability to be parallelised to enable satisficing performance for real-time applications such as intelligent industrial cyber-physical systems scheduling, autonomous control of distributed systems and active industrial informatics.
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Paper Nr: 25
Title:

IoT Natural Gas Pipeline Monitoring System
Authors:

Will Cook, Haley Felberg, Natalie Palos and James Yeh
Abstract: In this paper, we discuss our construction of a natural gas monitoring system that utilizes a network of nodes that communicate with each other using LoRa modulation techniques. After the devastating gas leak in 2015 at the Aliso Canyon Natural Gas Storage Facility in Los Angeles county, in which a total of 104,400 tonnes of methane and ethane gas was released into the atmosphere, it became apparent that gas storage facilities and pipelines are in need of more efficient gas leak observation and monitoring methods. Our solution involves constructing nodes from a LoRa32 microcontroller, MQ-4 gas sensor, solar panel, and a 3.7V lithium battery. The nodes will be configured in a daisy-chain topology that can be positioned along any pipeline or gas storage facility. The daisy-chain topology will allow data to be sent along the chain to a data collection node and subsequently stored in the cloud hosted Firebase database. It is also anticipated that this monitoring system will be surveyed using an intuitive mobile application for iOS and Android devices.
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Paper Nr: 26
Title:

Towards a Family of Digital Model/Shadow/Twin Workflows and Architectures
Authors:

Randy Paredis, Cláudio Gomes and Hans Vangheluwe
Abstract: Digital Twins (DTs) can be used for optimization, analysis and adaptation of complex engineered systems, in particular after these systems have been deployed. DTs make full use of both historical knowledge and of streaming data from sensors. DTs have been given numerous (distinct) definitions and descriptions in the literature. There is no consensus on terminology, nor a comprehensive description of workflows nor architectures. Following Multi-Paradigm Modelling principles, this paper proposes to explicitly model construction and use workflows of DTs as well as their architectures. We apply the concepts of variability (also known as product family) modeling, in particular to DT workflow and architecture. This allows for the de-/re-construction of the different DT variants in a principled, reproducible and partially automatable manner. To illustrate our ideas, two small use cases are discussed: a line-following robot (representative for an Automated Guided Vehicle) and an incubator (representative for an Industrial Convection Oven). The use cases focus on important systems in an industrial context.
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Paper Nr: 1
Title:

Manufacturing Process Simulation in a Hybrid Cloud Setup
Authors:

Gerhard B. Weiß, Dario Pietraroia, Claudio Sassanelli and Hugo D. Macedo
Abstract: Model-based design of manufacturing robotic systems involving the usage of different tools, models and the co-simulation of the system behaviour benefits from collaborative platforms enabling ready-to-use and cloud-hosted tools and models. Nonetheless, due to market segmentation and the difficulty to deploy and support all the existing tools and models in such a platform, it is, therefore, reasonable to consider a hybrid cloud-setup where some tools run in the public cloud and other are only available in private clouds or dedicated machines behind the walls of the licensed institution. In this paper, we report on a experiment of such scenario, where a Matlab/SimulinkTM, LS-Dyna, and Model.CONNECTTM powered co-simulation tool suite running in a private cloud is combined with the DDD Simulation tool running inside a public cloud. Due to this setup it was possible to combine a 1D hot stamping process simulation with a 3D visualisation. Finally the results of the process simulation were improved by considering realistic movement of the robot. Our study elicited several limitations and feature requests that need to be addressed to better support a hybrid cloud setup for model-based design practitioners. We expect this initial contribution to trigger ground breaking research encompassing all the community members interested in hybrid co-simulation setups.
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Paper Nr: 2
Title:

DigiMove Analysis for Manufacturing SMEs to Identify Their Current Status and next Digitalisation Steps
Authors:

Leila Saari, Risto Kuivanen and Jyrki Poikkimäki
Abstract: The digitalisation level of Finnish manufacturing companies must be improved in order to remain in Finland and keep the manufacturing industry competitive. Digitalisation was found to have a positive correlation with the business result. This was discovered by analysing the digitalisation level of 43 manufacturing companies in Finland. The analysis was performed with the DigiMove matrix, which contains the following six digitalisation subjects: i) Manufacturing, ii) Products and services, iii) Digital skills of production staff, iv) Foresight, v) Customer interface, and vi) Administrative functions. It also contains five maturity levels: i) General, ii) Improved, iii) Advanced, iv) Forerunner, and v) Future opportunity. Each cell in the matrix contains the description of the expected digital solutions to be used and implemented. These descriptions were discussed in detail with each company in the workshop, and their actual level of digitalisation was jointly defined. In addition to the instant analysis map created in the workshop, each company also received recommendations for their next digitalisation steps within a week. Subsequently, 43 DigiMove statistical analyses were conducted with the companies’ public financial data, and a positive correlation was found between digitalisation and the financial result.
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Paper Nr: 4
Title:

Interoperability Maturity Assessment of the Digital Innovation Hubs
Authors:

Concetta Semeraro, Hervé Panetto, Gabriel S. Leal and Wided Guédria
Abstract: In today’s manufacturing companies need to be able to join the Industry 4.0 paradigm and technologies. Often companies, especially SMEs are not digitally ready. Digital Innovation Hubs (DIHs) are raising for overcoming this problem. DIHs support companies providing services and digital technologies. However, the critical challenge, for the development of the DIHs ecosystem is to assess the ability of the DIHs and partners to interoperate together. DIH4CPS (Fostering DIHs for Embedding Interoperability in Cyber-Physical Systems of European SMEs) is an Innovation Action (IA) receiving funding from the European Union’s Horizon 2020 programme. DIH4CPS aims to create an embracing, interdisciplinary network of DIHs, and solutions providers, focused on cyber-physical and embedded systems, interweaving knowledge and technologies from different domains, and connecting regional clusters with the Pan-European expert pool of DIHs. The paper presents the concepts, the ontology, and the prototype developed for DIH4CPS project with the aim of assessing the Interoperability maturity of the DIHs and partner’s network.
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Paper Nr: 11
Title:

Blockchain Potential for Supply Chain Reconfiguration in Post COVID-19 Era
Authors:

Marco Ardolino, Beatrice Marchi, Maciel M. Queiroz, Andrea Bacchetti and Simone Zanoni
Abstract: The spread of the coronavirus has had a major impact on the global economy, highlighting the shortcomings and weaknesses of global supply chains. Major issues such as supply disruptions, shortages of raw materials and spare parts, restricted transport, and ineffective exchange of information between actors within the supply chain have resulted. The empirical evidence of these events is widely discussed in the literature, which has brought out the urgent need to rethink the configuration of customer-supplier relations at an overall level. One technology that is much discussed in the literature and potentially useful in supporting supply chain processes is the blockchain technology. Blockchain has been gaining attraction across different sectors, even if there are still few applications in supply chain management, most at an experimental level. The aim of this paper is to analyse the potential applications of blockchain to support supply chain processes, to fill the gaps highlighted during the Covid pandemic. Through the analysis of the literature, the authors aim to give a preliminary overview on the relationships between Covid-19 impacts and benefits achievable by the application of blockchain technology in the supply chain, for an effective supply chain reconfiguration in a post-covid era.
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Paper Nr: 24
Title:

Mobile-based Social Platform for Emergency Response Coordination
Authors:

Noha Mostafa, Abdalla Ashraf and Amr Eltawil
Abstract: The number of mortalities coming into the emergency room is still very high. While it is evident that the sooner professional medical assistance is provided the higher chances of survival, emergency response systems are yet to be improved and widely implemented to produce a significant impact. Mobile Applications are an important instrument to improve such a service. Mobile health (or ‘mhealth’) refers to healthcare and medical information that is supported by mobile technology. In 2015, approximately 80% of physicians used mobile devices and medical apps and 25% applied them to provide patient care. This study seeks implementing a design thinking approach to connect growing logistics and healthcare startups through an Information and Communication Technology (ICT) application and platform to provide a more efficient, effective and responsive emergency care through the coordination between emergency responders and the victim or rescuer at the point of incidence.
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Area 2 - Intelligent Manufacturing and Management

Short Papers
Paper Nr: 5
Title:

A Two-stage Genetic Algorithm for a Novel FJSP with Working Centers in a Real-world Industrial Application
Authors:

David Govi, Alessandro Rizzuto, Federico Schipani and Alessandro Lazzeri
Abstract: Inspired by industrial issues and demands, we define a novel version of the Flexible Job Shop Scheduling Problem with Working Center. A working center is a group of machines performing the same type of operation. The job operations of different types follow a strict sequence across the working centers, while any order is allowed among operations of the same type. This paper illustrates a genetic algorithm with a two-stage chromosome representation, adapted genetic operators, local search, and social disaster technique to deal with a real-world industrial application. The algorithm has been tested on a classical benchmark to assess its adaptability and compare its performance with state-of-the-art techniques; then, we tested different variations of the proposed algorithm on a real-case test instance showing a consistent improvement when compared with the heuristic in use at the industrial company.
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Paper Nr: 10
Title:

A Digital Twin-based Approach to the Real-time Assembly Line Balancing Problem
Authors:

L. Ragazzini, N. Saporiti, E. Negri, T. Rossi, M. Macchi and G. L. Pirovano
Abstract: The emergence of technologies linked to the Industry 4.0 paradigm is increasingly influencing the design and management of production systems. However, applications related to assembly lines are scarcely explored in the literature. Hence, in this paper, a Digital Twin-based approach to real-time assembly line balancing problem (ALBP) in the i-FAB learning factory of Università Carlo Cattaneo – LIUC is presented. The results show that the implementation of a Digital Twin (DT) can enhance the overall productivity of a manual assembly line to smooth the effects of disruptions.
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Paper Nr: 12
Title:

Efficacy of Statistical Formulations on Acoustic Emission Signals for Tool Wear Predictions
Authors:

Selvine G. Mathias and Daniel Grossmann
Abstract: Acoustic emission (AE) signals obtained during machining processes can be used to detect, locate and assess flaws in structures made of metal, concrete or composites. This paper aims to characterize AE signals using derived parameters from raw signatures along with statistical feature extractions to correlate with tool wear readings. Missing tool wear values are imputed using domain knowledge rules and compared to AE signals using machine learning models. The amount of effect on tool wear is formulated using Bayesian Inferences on derived parameters such as areas under the raw signal curve in addition to comparisons with the supervised models for predictions. Using the constructed models and formulation, the presented study also includes a trace-back pseudo-algorithm for determining the stage in process where tool wear values begin to approach the wear limits.
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Paper Nr: 6
Title:

Lead Time Estimation of a Drilling Factory with Machine and Deep Learning Algorithms: A Case Study
Authors:

Alessandro Rizzuto, David Govi, Federico Schipani and Alessandro Lazzeri
Abstract: This project is presented as a real case-study based on machine learning and deep learning algorithms which are compared for a clearer understanding of which procedure is more suitable to industrial drilling.The predictions are obtained by using algorithms with a pre-processed dataset which was made available by the industry. The losses of each algorithm together with the SHAP values are reported, in order to understand which features most influenced the final prediction.
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Paper Nr: 16
Title:

Digital Twins for Real-time Data Analysis in Industrie 4.0: Pathways to Maturity
Authors:

Philip Stahmann, Arne Krüger and Bodo Rieger
Abstract: Digital twins are virtual copies of production systems’ physical components. In Industrie 4.0, they represent a promising opportunity for analysing production data in real-time and contribute to improved production planning and control. However, development of digital twins is challenging for companies due to missing guidance. In this research paper, we identify four maturity levels for digital twins for real-time data analysis based on a structured literature review and a market analysis that resulted in a total of 82 analysed contributions. The results are evaluated through a qualitative interview with four experts from academia and practice. Manufacturing companies can use the maturity levels for self-assessment and as a guideline. Future research can use the maturity levels for integration into holistic maturity models.
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Area 3 - Logistics and Operations Research

Full Papers
Paper Nr: 9
Title:

Online Metric Facility Service Leasing with Duration-Specific Dormant Fees
Authors:

Christine Markarian and Peter Khallouf
Abstract: Inspired by the COVID-19 pandemic, a new online facility model, known as the Online Facility Service Leasing problem (OFSL), has been recently introduced. In OFSL, services at different (health) facility locations are leased for different durations and costs. Each service at each facility is associated with a dormant fee that needs to be paid for each day on which the service is not leased at the facility. Clients arrive over time, each requesting a number of services, and need to be served by connecting them to multiple facilities jointly offering the requested services. The aim is to decide which services to lease, when, and for how long, in order to serve all clients as soon as they appear with minimum costs of leasing, connecting, and dormant fees. In this paper, we study a generalization of OFSL in which we are additionally given a parameter d, such that, should the service be not leased for more than d consecutive days, a dormant fee is to be paid (d = 0 in the case of OFSL). We call this variant the Online Facility Service Leasing with Duration-Specific Dormant Fees (d-OFSL). We particularly focus on the metric version of the problem in which facilities and clients reside in the metric space. We refer to it as metric d-OFSL and design the first online algorithm for the problem. The latter is a deterministic algorithm based on a primal-dual approach. We measure its performance by comparing it to the optimal offline solution for all instances of the problem. This performance analysis is known as competitive analysis and is the standard to evaluate online algorithms.
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Paper Nr: 17
Title:

Tailoring a Red Deer Algorithm to Solve a Generalized Network Design Problem
Authors:

Imen Mejri, Safa Bhar Layeb and Emna Drira
Abstract: This work investigates solving a challenging network design problem using the recently introduced evolutionary metaheuristic, namely the Red Deer Algorithm (RDA), that mimics the Scottish Red Deer’s behavior during their breeding season. The RDA is tailored to solve a generalized network design problem that aims to design a network with minimal cost while satisfying several practical constraints. To assess the performance of this new bio-inspired metaheuristic on solving such NP-hard problem, computational experiments were conducted on Benchmark as well as real-world instances. Computational experimentation illustrates the accuracy of the RDA that outperforms all of the existing recent metaheuristics.
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Paper Nr: 27
Title:

Online Set Cover with Happiness Costs
Authors:

Christine Markarian
Abstract: The Online Set Cover problem (OSC) and its variations are one of the most well-studied optimization problems in operations research and computer science. In OSC, we are given a universe of elements and a collection of subsets of the universe. Each subset is associated with a cost. As elements arrive over time, the algorithm purchases subsets to cover these elements. In each step, an element arrives, and the algorithm needs to ensure that at the end of the step, there is at least one purchased subset that contains the element. The goal is to minimize the total cost of purchased subsets. In this paper, we study a generalization of OSC, in which a request consisting of a number of elements arrives in each step. Each request is associated with a happiness cost. A request is served by either a single subset containing all of its elements or by a number of subsets jointly containing all of its elements. In the latter case, the algorithm needs to pay the happiness cost associated with the request. The goal is to serve all requests upon their arrival while minimizing the total cost of purchased subsets and happiness costs paid. This problem is motivated by intrinsic service-providing scenarios in which clients need not only be served but are to be satisfied with the service. Keeping clients happy by serving them with one service provider rather than many, is represented by happiness costs. We refer to this problem as Online Set Cover With Happiness Costs (OSC-HC) and design the first online algorithm, which is optimal under the competitive analysis framework. The latter is a worst-case analysis framework and the standard to measure online algorithms. It compares, for all instances of the problem, the performance of the online algorithm to that of the optimal offline algorithm that is given all the input sequence at once and is optimal.
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Short Papers
Paper Nr: 14
Title:

Use of a Virtual Twin for Dynamic Storage Space Monitoring in a Port Terminal
Authors:

Andreas Höpfner, Olaf Poenicke, Christian Blobner and André Winge
Abstract: The paper describes research and development for dynamic 3D models and Virtual Reality (VR) applications in the context of port processes. The work described is carried out in the currently ongoing EU-funded project PortForward. The paper addresses the use of VR technologies in the context of industrial applications and describes how dynamic sensor data can be integrated into a 3D model of a Port. In addition to tracking data of moving assets, the sensor data mainly comprises 3D measurement data from LiDAR sensors. These sensors are installed in the port infrastructure to automatically record the current occupancy status of storage areas. The measurement data from the LiDAR sensors are dynamically integrated into the VR model in an abstracted form together process related meta-data to reflect the current process status in the port terminal. Based on that approach in the sense of a Virtual Twin, process flows and storage space management can be optimized. The use of VR technologies is crucial in this context in order to depict the complex spatial and dynamic process situation in an intuitive way.
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