On the Relationship between Circular and Innovation Approach to Economy

MDPI Sustainability
Published on: 26 – 10 – 2021
A publication from LMS

The first and most important target of the industrial world is to offer products that appeal to customers’ demands (affordable prices), while at the same time, respect the global effort of CO2 emissions reductions, which is required under strict emissions rules. There is, however, an apparent contradiction between the two concepts; productivity and sustainability, leading to two strategies—innovation economy and circular economy, respectively. To this end, this work aims, through modeling the long-term environmental impact of producing new goods in short terms (innovation economy) and impact of rebuying, repairing and reusing products for extended use (circular economy), to study the relationship between the two economies. For this purpose, the terms of innovation and circular economy are introduced and described, in order to define the environmental impact during the lifecycle of a product. Two products are assessed for this study—a well-known, medium price vehicle, as well as an expensive mobile phone with several generations. The cost of purchase and the recurring costs are used as indicators of environmental impact, instead of calculating the impact directly for the production phase, due to the enormous size of the production data that are desired. The results, despite being indicative of the modelling complexity, can still be used to pave the way towards a modelling framework, proving, at the same time, that innovation and circular economy are not contradictive concepts.

Manufacturing resilience and agility through processes digital twin: design and testing applied in the LPBF case

Conference: 9th CIRP Global Web Conference – Sustainable, resilient, and agile manufacturing and service operations: Lessons from COVID-19 of Metal Additive Manufacturing Processes
Published on: 20 – 10 – 2021
A publication from LMS

The paper investigates the integration of different models under the scope of a digital twin for the case of additive manufacturing. The proposed framework takes into account all the phases of the digital twin such as sensors, modeling, diagnostics, and prognostics functions. An implementation of the digital twin platform is done through a deep learning algorithm for real-time prediction. The performance of the platform has a good agreement in terms of feasibility, capabilities, and execution time.

An AR based Digital Twin for Laser based manufacturing process monitoring

18th CIRP Conference on Modeling of Machining Operations (CMMO), Ljubljana, Slovenia, June 15-17, 2021
Published on: 27 – 09 – 2021
A publication from LMS

In the modern manufacturing era, monitoring systems evolve towards sophistication and complexity, introducing numerous challenges in the feasibility, the assembly, the efficiency, and the integration of process monitoring devices on the relative equipment. The current work introduces a novel digital AR based digital twin framework, enabling real-time information analysis and advanced data visualization of monitoring performance on process monitoring systems. The main goal of the current research is to provide a dynamic AR environment, capable of simulating the main system’s functionalities, minimizing the configuration time, cost, and inaccuracies. The case study introduced regards the configuration of optics for thermal emissions capturing from laser based processes, while the coexistence with other aspects of monitoring, such as in the case of Remote Laser Welding is considered. The usability of the tool is shown and visualization issues encountered are presented.

Industry 4.0 Concept for small series electric car production

XXIX Technical & Science Conference “Design & Exploitation of Electrical Machines & Drives”
Published on: 23 – 09 – 2021
A publication from POLEVS

The paper presents the results of the analysis of the program: “Polish Electromobility Development“, the forecasts and the diagnoses and its causes from private investor point of view. The concept of developing EV production outside large corporations OEM will be presented. This concept bases on a chain of SME suppliers, working in network in I4.0 concept, whose products will fill the gap in the development of green transport. The electromobility should be an important element of the development strategy, and would have to impact on improving the live standard in cities and in suburban and rural areas as well. Electric vehicles together with the infrastructure will contribute in stabilization of the energy network and improve its reliability by buffering. But for the system, the “true car”, which will satisfy the customer needs is needed. The production of electric cars, like production of combustion vehicles in OEM, is too expensive. It would never break the barrier of users volume. This problem concerns others countries in the EU. For this reason, an international consortium was founded for AVANGARD project. The paper will present the assumptions and planned course of this project with expected benefits for Polish companies.

A critical review on the environmental impact of manufacturing: a holistic perspective

The International Journal of Advanced Manufacturing Technology
Published on: 07 – 09 – 2021
A publication from LMS

Manufacturing sector is considered to be the second highest contributor in greenhouse gases emissions in EU, secondary to energy sector. The environmental impact of products, processes, and infrastructures of manufacturing is defined as the mass equivalent of carbon dioxide emissions, also known as carbon footprint, because carbon dioxide accounts for the largest portion of greenhouse gases emissions. The aim of this review is to show the impact of manufacturing on carbon emissions and to investigate the importance of carbon emission factors on the carbon footprint of manufacturing. This was performed via (1) mapping and categorizing the sources of carbon emission at process, machine, and system level; (2) identifying the weight factor of carbon emissions factors via sensitivity analysis; and (3) determining which carbon emission factor has the heaviest contribution in carbon footprint calculation. In all examples of the sensitivity analysis, it was shown that carbon emission factor for electrical energy was the only contributing factor at process level while being the strongest at machine level. At system level, the strongest contributor was the carbon emission factor for material production. To reduce the carbon emissions, one must identify the tuneable parameters at process, machine, and system level, from material, machine tool, and energy point of view. However, the highest reduction in carbon footprint can be achieved by reducing the carbon emission factors of electrical energy using renewable power sources such as solar or wind and by reducing the carbon emission factors for material production using recycling materials as “raw” material.

On the Impact of Additive Manufacturing Processes Complexity on Modelling

MDPI – Applied Sciences as a Special Issue on Additive Manufacturing
Published on: 23 – 08 – 2021
A publication from LMS

The publication proposed a metamodeling framework for AM is presented, aiming to increase the practicality of simulations that investigate the effect of the movement of the head on part quality. The existing AM process groups have been classified based on three parameters/axes: temperature of the process, complexity, and part size, where the complexity has been modelled using a dedicated heuristic metric, based on entropy. To achieve this, a discretized version of the processes implicated variables has been developed, introducing three types of variables: process parameters, key modeling variables and performance indicators. This can lead to an enhanced roadmap for the significance of the variables and the interpretation and use of the various models. The utilized spectrum of AM processes is discussed with respect to the modelling types, namely theoretical/computational and experimental/empirical.

A two-stage decision support system for manufacturing processes integration in microfactories for electric vehicles

Conference: 10th CIRP Sponsored Conference on Digital Enterprise Technologies (DET 2020) – Digital Technologies as Enablers of Industrial Competitiveness and Sustainability
Published on: 30 – 07 – 2021
A collaborative publication from LMS & IFEVS

Integrating a manufacturing process is not a straightforward decision. Involved cost models are complex covering the whole lifecycle of the part in the context of circular economy. In this work, given the complexity of circular industry and the modularity required in the case of electric vehicles, a framework for a dedicated decision support system is presented. A case study for a microfactory is presented. The two stages of the decision-support system (DSS) are applied, with the first one proving empirically the feasibility of the technology integration and the second one involving a detailed cost model for assessment of the return of investment (ROI).

Eco-friendly approach to electro-mobility (Avangard approach)

MATEC Web Conference: 34th Scientific Conference: Problems of Working Machines Development (PRMR 2021)
Published on: 25 – 06 – 2021
A publication from POLEVS

The paper presents the issues of ecological use of electric vehicles, comparing the combustion and electric environmental studies. An analysis of the common electric vehicle structures and their operation will be presented, in which the environmental performance of vehicles and their positive impact on the quality of life can be achieved or enhanced by a new approach to the design, production and servicing method. In the described model of vehicle production, which can be extended to the manufacturing of small agricultural and municipal machines, new methods of design (using artificial intelligence) and production, including 3D printing and others, play an important role. The authors will present several technologies used in small-lot production and a forecast of their use.

Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring

MDPI Energies as a Special Issue on Manufacturing Energy Efficiency and Industry 4.0
Published on: 17 – 06 – 2021
A collaborative publication from UNINOVA and INTROSYS

The paper presents an interoperable solution based on events to reduce the complexity of integration, while creating energetic profiles for the machines to allow the optimization of their energy consumption. A publish/subscribe-based architecture is proposed, where the instantiation is based on Apache Kafka. The proposed solution was implemented in two robotic cells in the automotive industry, constituted by different hardware, which allowed testing the integration of different components. The energy consumption data was then sent to a Postgres database where a graphical interface allowed the operator to monitor the performance of each cell regarding energy consumption. The results are promising due to the system’s ability to integrate tools from different vendors and different technologies. Furthermore, it allows the possibility to use these developments to deliver more sustainable systems using more advanced solutions, such as production scheduling, to reduce energy consumption.

Steps from Zero Carbon Supply Chains and Demand of Circular Economy to Circular Business Cases

European Journal of Social Impact and Circular Economy
Published on: 19 – 07 – 2021
A publication from SPHERA

The paper presents approaches and companies seeking carbon neutral product in a carbon neutral Europe via identifying business cases for circular products. An evaluation matrix is presented allowing the identification of circularity status depending on the selected products or sector perspective. The goal is to avoid trade-offs and to consider economic and environmental factors side by side. The presented approach combines life cycle assessment, circular economy and the development of business models and is partly developed and applied.

Secure Asset Tracking in Manufacturing through Employing IOTA Distributed Ledger Technology

Conference: 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid)
Published on: 12 – 5 – 2021
A publication from HMU-STM

Today, manufacturing industry is increasingly embracing new technologies such as the Internet of Things (IoT), big data analytics, cloud computing and cybersecurity to cope with system complexity, increase information visibility, improve production performance, and gain competitive advantages in the global market. These advances are rapidly enabling a new generation of smart manufacturing, i.e., a cyber-physical system tightly integrating manufacturing enterprises in the physical world with virtual enterprises in cyberspace. To a great extent, realizing the full potential of cyber-physical systems depends on the development of new methodologies on the Internet of Manufacturing Things (IoMT) for data-enabled engineering innovations. This article presents a real implementation of IOTA Tangle architecture for data transactions extended with HMAC signing through using STM32 (F7 CPU) IoT devices. The evaluation results show promising with 32 light nodes to exceed 28 transactions per second by using 4 full nodes, thus making IOTA-based distributed ledger an effective solution for IoT-based manufacturing environments with zero-value (data) transactions.

From Hardware-Software Contracts to Industrial IoT-Cloud Block-chains for Security

Conference: 2021 Smart Systems Integration (SSI)
Published on: 28 – 4 – 2021
A publication from HMU-STM

In the era of smart factories, to embrace IoT devices attached to physical assets, we need to guarantee control and complete confidence in how the data they share are used. This work introduces hardware mechanisms to ensure security in terms of secure key and signature storage through RFID/NFC secure modules and an IoT infrastructure communicating over LoRaWAN in conjunction with Hyperledger Fabric for traceability and immutability. A practical implementation is presented and evaluated with an average throughput of more than 70 transactions/sec for 16 peers.

Robust Additive Manufacturing Performance through a Control Oriented Digital Twin

MDPI-Metals as a Special Issue on Optimization of Metal Additive Manufacturing Processes
Published on: 26 – 04 – 2021
A publication from LMS

The additive manufacturing process control utilizing digital twins is an emerging issue. However, robustness in process performance is still an open aspect, due to uncertainties, e.g., in material properties. To this end, in this work, a digital twin offering uncertainty management and robust process control is designed and implemented. As a process control design method, the Linear Matrix Inequalities are adopted. Within specific uncertainty limits, the performance of the process is proven to be acceptably constant, thus achieving robust additive manufacturing. Variations of the control law are also investigated, in order for the applicability of the control to be demonstrated in different machine architectures. The comparison of proposed controllers is done against a fine-tuned conventional proportional–integral–derivative (PID) and the initial open-loop model for metals manufacturing. As expected, the robust control design achieved a 68% faster response in the settling time metric, while a well-calibrated PID only achieved 38% compared to the initial model.

Automation for Industry 4.0 by using Secure LoRaWAN Edge Gateways

Book Chapter: Multi-Processor System-on-Chip: Vol. 2 – Applications
Published on:
A collaborative publication from STM and HMU

The chapter presents the key concepts required to implement a security architecture to enable complete IIoT security in a LoRaWAN environment, through the use of in-depth analysis of methods. The LoRaWAN gateway is realized through integrating the RAK831 RF front-end LoRaWAN gateway concentrator module with the host system STM32MP1-DK2 connected via SPI. The threat model involves attacks seeking to perform malicious network or firmware attacks, by sniffing and replaying network traffic, by modifying the IoT node firmware or by injecting malicious code into the firmware, the operating system or the kernel driver.

On the generation of validated manufacturing process optimization and control schemes

CIRPe 2020 – 8th CIRP Global Web Conference – Flexible Mass Customisation
Published on: 14 – 10 – 2020
A publication from LMS

Manufacturing process related functionalities, like optimization and control, are in general demanding in terms of data, computational time and efficiency. However, there are no generic certification or validation schemes that can be followed. In particular, only ISO application can verify the suitability of operations up to an extent. The current work utilizes an enhanced version of Blockchain so that functionalities at the process level can be certified as per a particular scheme. The concept of ledger is elaborated to this end, to manipulate knowledge and be able to handle it like an asset that is exchanged. Thus, a specific generic framework is proposed, herein, to reassure that the right kind of information has been exchanged during process control and optimization. Furthermore, expert distributed agents are utilized to turn knowledge into certified procedures. Encryption issues are also regarded, providing safety and security as extra characteristics. The case study of thermal process control is regarded in this sense to prove the complementary character of these concepts and the usability of the framework. Finally, the existence of additional features within this loop is discussed, like the validation of quantifying concepts like resource streams.

Combining process and machine modelling: A Cold Spray Additive Manufacturing case

Conference: 20th CIRP Conference on Electrophysical and chemical machining
Published on: 02 – 02 – 2020
A publication from LMS

Cold Spray is a new addition to the Additive Manufacturing field that uses the kinetic energy of unmelted sprayed particles to build the layers. The process simulation for obtaining the velocity range of the particles is key for improving the adhesion quality. In this study, a modeling approach is presented that divides the overall process into two separate sections calculating in a reasonable time if the initial conditions are suitable. The first section comprises a CFD model from which the velocity range is acquired and the second section comprises an FEA simulation of the particles’ impact on the deposition plate.

Manufacturing Resilience during the Coronavirus Pandemic: On the investigation Manufacturing Processes Agility

European Journal of Social Impact and Circular Economy
Published on: 18 – 12 – 2020
A publication from LMS

The unprecedented eventsthatworldwide population experiencedduring year 2020 due to the COVID-19 pandemic, resulted in the formation of numerous challenges across the majority of aspects of every day life. The journal investigates to identify the challenges of traditional manufacturing methods in the Coronavirus Pandemic and proposed a framework where Additive Manufacturing can produce vital components instantly and at a low production. To assess the presented methodology, a comparison between two different manufacturing methods for the production of a respiratory component has been used as case study. Finally,a hybrid manufacturing model is suggested.

Manufacturing Process Control Through a Digital Twin: Encoding Issues

Conference: TESConf 2020 – 9th International Conference on Through-life Engineering Services
Published on: 26 – 10 – 2020
A publication from LMS

A Manufacturing Process Digital Twin is highly useful in Process Control, since it shows adaptiveness and near-real-time responsivity. However, cloud architectures are in place, or more commonly, CPS-based modules communicate through IoT technology, implicating security (data-related) and safety (concerning proper control enforcement). With respect to Thermal Processes, and in particular Laser Welding, this work studies the effect of encoding on Process Control efficiency. More specifically, compression and encryption are applied to control signals and the process control efficiency is studied. The simulations used to this end are considered to be part of a digital twin.

A three-stage quality diagnosis platform for laser-based manufacturing processes

The International Journal of Advanced Manufacturing Technology
Published on: 18 – 09 – 2020
A publication from LMS

Diagnosis systems for laser processing are being integrated into industry. However, their readiness level is still questionable under the prism of the Industry’s 4.0 design principles for interoperability and intuitive technical assistance. This paper presents a novel multifunctional, web-based, real-time quality diagnosis platform, in the context of a laser welding application, fused with decision support, data visualization, storing, and post-processing functionalities. The platform’s core considers a quality assessment module, based upon a three-stage method which utilizes feature extraction and machine learning techniques for weld defect detection and quality prediction. A multisensorial configuration streams image data from the weld pool to the module in which a statistical and geometrical method is applied for selecting the input features for the classification model. A Hidden Markov Model is then used to fuse this information with earlier results for a decision to be made on the basis of maximum likelihood. The outcome is fed through web services in a tailored User Interface. The platform’s operation has been validated with real data.

Employing bibliometric analysis to identify suitable business models for electric cars

Journal of Cleaner Production
Published on: 18 – 04 – 2020
A publication from UNITO

Business model architectures in the car industry are gaining increased attention from scientists and policymakers. Although scientific studies have been conducted to address the pressures faced by future business models to change, no research has examined the bibliometric variables in this area. This study aims to fill the gap by conducting a bibliometric analysis of 104 articles on business models for electric cars. The analysis showed that the literature on business models for electric cars is exhaustive, and it focuses on business model decisions for charging technologies, driver services, electricity management, commercial contracts, and plant. China, the United States of America, and Germany have conducted the maximum number of studies on the aforementioned theme. The topic dendrogram identified two evolving strands of discussions and innovative technologies and resource optimization and electricity management systems and product life cycle. These findings can guide the formulation of environmentally sustainable policies for electric car manufacturing and help car manufacturers to restructure their models.