IN4PL 2020 Abstracts

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

Area 1 - Industry 4.0

Full Papers
Paper Nr: 13
Title:

Semantic Web Services for AI-Research with Physical Factory Simulation Models in Industry 4.0
Authors:

Lukas Malburg, Patrick Klein and Ralph Bergmann
Abstract: The transition to Industry 4.0 requires smart manufacturing systems that are easily configurable and provide a high level of flexibility during manufacturing in order to achieve mass customization or to support cloud manufacturing. To realize this, Cyber-Physical Systems (CPSs) combined with Artificial Intelligence (AI) methods find their way into manufacturing shop floors. For using AI methods in the context of Industry 4.0, semantic web services are indispensable to provide a reasonable abstraction of the underlying manufacturing capabilities. In this paper, we present semantic web services for AI-based research with physical factory simulation models in Industry 4.0. Therefore, we developed 70 semantic web services based on Web Ontology Language for Web Services (OWL-S) and Web Service Modeling Ontology (WSMO) and linked them to an already existing domain ontology for intelligent manufacturing control. Suitable for the requirements of CPS environments, our pre- and postconditions are verified in near real-time by invoking other semantic web services in contrast to complex reasoning within the knowledge base. Finally, we examine the feasibility of our approach by executing a cyber-physical workflow composed of semantic web services using a state-of-the-art workflow management system.
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Short Papers
Paper Nr: 1
Title:

Insights into SoRa: A Reference Architecture for Cyber-physical Social Systems in the Industry 4.0 Era
Authors:

Teodor Ghetiu and Bogdan-Constantin Pirvu
Abstract: Reference architectures for Industry 4.0 tend to have a techno-centric orientation; their social dimension is usually restricted to specifying that users exist, and they have concerns that impact the architecture of desired systems. We take a step further to make the social element the core of future systems. A first step is to propose a reference architecture for Industry 4.0 cyber-physical social systems (CPSS), that builds upon proposals from well-known initiatives. Key differentiator in our design is the explicit consideration of the human – cyber-physical relation and the way the two sides influence or adapt to each other. The final aim is that architecture descriptions derived from this reference architecture, will enable the development of CPSSs capable of harnessing the power of the Internet of Things (IoT), while respecting the importance of their human members.
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Paper Nr: 2
Title:

Circular Economy-oriented Simulation: A Literature Review Grounded on Empirical Cases
Authors:

Claudio Sassanelli, Paolo Rosa and Sergio Terzi
Abstract: Nowadays, manufacturers are increasingly impelled in adopting Circular Economy (CE) strategies and consistently adequating their business models to more environment-oriented practices. However, several barriers can be encountered during the transition from linear to circular behaviours. Here, simulation methods can play a strategic role in supporting companies during the assessment of potential solutions to make their products’ lifecycle circular. To this aim, simulation (as part of Industry 4.0 (I4.0) technologies), have been detected through a literature review as one of the main technologies supporting CE. Basing on results, the End-of-Life (EoL) stage seems to play a strategic role within CE practices, with disassembly processes as the enabler for most of these circular strategies (e.g. reuse, reman, recycle, etc.). Moreover, a big focus is on how to foster CE through the improvement of disassembly processes of Waste from Electrical and Electronic Equipment (WEEEs) and Printed Circuit Boards (PCBs). Hence, a deeper analysis of how simulation approaches can contribute to enhance these processes is presented, by defining those technologies needed to improve specific product lifecycle stages.
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Paper Nr: 4
Title:

Infrastructure for an Integrated Industry 4.0 Life Cycle Spanning Design and Production Platform
Authors:

Robert Mühlbacher, Hans Göpfrich and Andràs Gàlffy
Abstract: This paper proposes an infrastructure for the digitalisation and integration of tasks along the life cycle of a lotsize-1 product from specification to depollution. The proposal shows the integration of existing open source tools into a design and production infrastructure. Starting from the positioning of the approach within the RAMI 4.0 framework, additional abstraction layers are presented, which help to organize the life cycle process. Besides the layer conception a showcase implementation is presented, which provides a factory for the production of model airplanes. The prototype shows the life cycle of a product instance as it is specified down to the production and even further. The digital twin convoys the instance along its whole existence.
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Paper Nr: 5
Title:

Evaluation of a Service System for Smart and Modular Special Load Carriers within Industry 4.0
Authors:

Johannes Zeiler, Anja Mecklenburg and Johannes Fottner
Abstract: Current research approaches in the field of logistics discuss the transformation of load carriers into smart objects. These so-called cyber physical systems collect data, aiming for process optimisation and increased transparency. Though special load carriers are commonly used in the automotive industry and have great potential in terms of digitalisation, they are mostly neglected. Understocking and overstocking, as well as production stops due to missing or damaged containers can result from insufficient transparency in supply chains. This paper presents the benefit and usability evaluation of a service system with smart and modular special load carriers, which aims to counteract this lack of transparency by providing databased services. In the therefore concluded web-based survey, experts evaluated the identified benefits in terms of impacts on the process, the customer and the environment. The presented results show that the benefits generated by the service system are suitable for optimising the conditions for the logistic process, the customer, the environment and the transparency within the supply chain. Although the already implemented functionalities of the service system are still limited in usability, the theoretical concepts and its functionalities have great potential in terms of future applications.
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Paper Nr: 11
Title:

Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0
Authors:

Fabian Berns, Markus Lange-Hegermann and Christian Beecks
Abstract: Discerning unexpected from expected data patterns is the key challenge of anomaly detection. Although a multitude of solutions has been applied to this modern Industry 4.0 problem, it remains an open research issue to identify the key characteristics subjacent to an anomaly, sc. generate hypothesis as to why they appear. In recent years, machine learning models have been regarded as universal solution for a wide range of problems. While most of them suffer from non-self-explanatory representations, Gaussian Processes (GPs) deliver interpretable and robust statistical data models, which are able to cope with unreliable, noisy, or partially missing data. Thus, we regard them as a suitable solution for detecting and appropriately representing anomalies and their respective characteristics. In this position paper, we discuss the problem of automatic and interpretable anomaly detection by means of GPs. That is, we elaborate on why GPs are well suited for anomaly detection and what the current challenges are when applying these probabilistic models to large-scale production data.
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Paper Nr: 15
Title:

Position Paper: Low-cost Prototyping and Solution Development for Pandemics and Emergencies using Industry 4.0
Authors:

Srihari Yamanoor, Narasimha S. Yamanoor and Satyakanth Thyagaraja
Abstract: Pandemics, such as the coronavirus pandemic and other large-scale public emergencies, including floods, volcanic explosions, and earthquakes, require strategic responses for smooth function and restart of industry. Creative, robust, low-cost, scalable solutions must be deployed for underserved and socially disadvantaged communities. This effort requires compressing product and process development from requirements engineering to final testing and deployment, service, and repair, in terms of timeframes, budgets, and related resource constraints. Exceptional circumstances, such as the coronavirus pandemic, add additional pressures such as social-distancing requirements. Several development techniques and tools are available for teams to respond rapidly and effectively to evolving needs in a cost and resource-efficient manner. Industry 4.0 principles can be extended to support frugal development, manufacturing, and operations in diverse communities. Efforts such as the Maker Movement and the availability of licensing techniques for open hardware and software development further add to the abilities of teams to enable virtual collaboration, solution development, customization, and deployment. The paper describes two positions, one that Industry 4.0 can aid in frugal solution development for underserved communities, and two that Industry 4.0 can be implemented frugally to aid production and quality among underserved and vulnerable communities.
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Paper Nr: 17
Title:

Time to Change: Considering the 4th Industrial Revolution from Three Sustainability Perspectives
Authors:

André Ullrich and Norbert Gronau
Abstract: Industry 4.0 leads to a radical change that is progressing incrementally. The new information and communication technologies provide many conceivable opportunities for their application in the context of sustainable corporate management. The combination of new digital technologies with the ecological and social goals of companies offers a multitude of unimagined potentials and challenges. Although companies already see the need for action, there was in the past and currently still is a lack of concrete measures that lever the potential of Industry 4.0 for sustainability management. During the course of this position paper we develop six theses (two from each sustainability perspective) against the background of the current situation in research and practice, and policy.
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Paper Nr: 18
Title:

Implementation and Evaluation of MES in One-of-a-Kind Production
Authors:

Giulia Bruno, Franco Lombardi and Mattia Orlando
Abstract: Customers are demanding more and more a product of high quality and fast delivery at a low price, while simultaneously expecting that the product meets their individual needs and requirements. For companies characterized by a highly customized production, it is essential to optimize the use of machines and reduce the production cycle. The aim of this paper is to develop and evaluate how a MES is able to collect data from the machines and use such data to perform a real time planning of production activities. The system has been implemented in an Italian company that produces metal sheet components for prototypes and small series in the automotive sector, which is characterized by a production with high complexity and high mix of products. The obtained results show that the system provides several benefits in term of reduction of times.
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Paper Nr: 19
Title:

Balancing of Manual Reconfigurable Assembly Systems with Learning and Forgetting Effects
Authors:

Maria A. Butturi, Francesco Lolli and Chiara Menini
Abstract: Within the paradigm of Industry 4.0, digital reconfigurable manufacturing and assembly systems can rapidly adapt to dynamic market demand, modifying their capacity and functionality. In manual or hybrid reconfigurable assembly systems, the rapid and frequent variations in the performed tasks subject workers to a significant cognitive load, making relevant the learning-forgetting phenomenon. In fact, the operators carry out the assigned activities for a short time before a reconfiguration of the system takes place, assigning them tasks often different from those just performed. This paper aims at investigating how the tasks’ execution time varies for operators working along a reconfigurable assembly line, depending on the learning forgetting effect. We applied a Kottas-Lau algorithm, considering the expected execution times updated according to a learning-forgetting curve. A numerical example, considering with five successive reconfigurations, allows to analyse the expected execution time trend for each operator-task pair and the variation in costs obtained as the operators learning rate and the variability of the operations change.
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Area 2 - Intelligent Manufacturing and Management

Full Papers
Paper Nr: 7
Title:

Validating Results of 3D Finite Element Simulation for Mechanical Stress Evaluation using Machine Learning Techniques
Authors:

Alexander Smirnov, Nikolay Shilov, Andrew Ponomarev, Thilo Streichert, Silvia Gramling and Thomas Streich
Abstract: When a new mechanical part is designed its configuration has to be tested for durability in different usage conditions (‘stress evaluation’). Before real test samples are produced, the model is checked analytically via 3D Finite Element Simulation. Even though the simulation produces good results, in certain conditions these could be unreliable. As a result, validation of simulation results is currently a task for experts. However, this task is time-consuming and significantly depends on experts’ competence. To reduce the manual checking effort and avoid possible mistakes, machine learning methods are proposed to perform automatic pre-sorting. The paper compares several approaches to solve the problem: (i) machine learning approach, relying on geometric feature engineering, (ii) 2D convolutional neural networks, and (iii) 3D convolutional neural networks. The results show that usage of neural networks can successfully classify the samples of the given training set.
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Paper Nr: 10
Title:

Exploitation Efficiency System of Crane based on Risk Management
Authors:

Janusz Szpytko and Yorlandys S. Duarte
Abstract: The subject of the paper is the exploitation efficiency system of overhead type cranes operating in critical systems, results implementation the control risk management and maintenance scheduling processes. The study case of the paper is a hot rolling mills system of a steel plant with critical overhead cranes operating with hazard conditions and continuous operation. The model output is an optimal overhead cranes maintenance scheduling distribution minimizing the production line risk stopped and the model input is a digital database structure with historical information related with the operation, maintenance, logistics and management process of the overhead cranes in the hot rolling mills plant. The transfer function is a stochastic non-linear optimization model with bounded constraint that assess a risk global-system indicator based on Monte Carlo simulations.
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Short Papers
Paper Nr: 3
Title:

Assessing Project Progress Planning using Control Diagrams and Neural Network Prediction for Shipbuilding Projects in an Ecuadorian Shipyard
Authors:

Gerardo M. Caceres
Abstract: The planning and scheduling of new shipbuilding projects, as in other engineering disciplines require a certain degree of experience and knowledge in order to provide progress planning of feasible works to achieve the goals of the project and the managerial expectation. As is mentioned, although having experience is necessary; according to current technologies, the use of data analysis and the certainty that in the medium-term future artificial intelligence will be used in decision-making, it is necessary that not only manufacturing be according to the approaches of industry 4.0 but also, project management from its start-up phase to closure uses mechanisms for continuous improvement in a more successful way. This case study focuses on the data analysis of planned and executed projects to estimate acceptable percentages of periodic progress of projects using parameters of reliability engineering and neural network model from ISPP IBM software, in such a way that the planning can be in accordance with the shipyard behaviour.
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Area 3 - Logistics and Operations Research

Short Papers
Paper Nr: 12
Title:

IoT Data Analytics in Retail: Framework and Implementation
Authors:

Jānis Grabis, Kristina Jegorova and Krišjānis Pinka
Abstract: IoT data analytics has many potential applications in the retail industry. However, relations among ambient conditions at stores as measured by IoT devices and sales performance are not well understood. This paper explores sensory and sales data provided by a large retail chain to quantify the impact of air quality, temperature, humidity and lighting on customer behaviour. It has been determined that the air quality and humidity have a significant impact and temperature appears to have a non-linear effect on customer behaviour. The data analysis findings are used to configure an IoT data analytics platform. The platform is used to monitor the ambient conditions in retail stores, to evaluate a need for improving the conditions as well as to enact improvement by passing them over to a building management system.
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