{"title":"A Layer Image Auditing System Secured by Blockchain","authors":"Jinwoo Song, Young Moon","doi":"10.1016/j.promfg.2021.06.059","DOIUrl":"10.1016/j.promfg.2021.06.059","url":null,"abstract":"<div><p>In Additive Manufacturing (AM), auditing layer-by-layer images can detect infill defective attacks effectively. However, the auditing process itself can become a target of inside or outside attackers in Cyber-Physical Manufacturing System (CPMS) environments because pervasive connection through various types of computer networks in CPMS opens new doors for adversaries to compromise various components in an attack detection system. To maintain an effective attack detection system and prevent data from malicious data injection, this paper presents a Layer Image Auditing System (LIAS) secured by the Blockchain technology in CPMS. LIAS consists of a pre-processing system and a Multilayer Perceptron Neural Network (MLP). To evaluate the prediction accuracy of LIAS, a set of simulated infill images and physical images were used for training and testing. The effectiveness of the Blockchain implementation is demonstrated by presenting the comparative performance analysis of the proposed attack detection system with and without the Blockchain.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":"53 ","pages":"Pages 585-593"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54984117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Teaching Manufacturing Processes from an Innovation Perspective","authors":"Brian K. Paul , Laine Mears , Albert Shih","doi":"10.1016/j.promfg.2021.06.076","DOIUrl":"10.1016/j.promfg.2021.06.076","url":null,"abstract":"<div><p>The manufacturing innovation that underlies advanced products comes about through rational, reasoned design, motivating the need for a manufacturing engineering curriculum within higher education that teaches methodologies for designing manufacturing processes. As an alternative to conventional manufacturing process courses, the authors propose learning outcomes and methods for teaching process design and innovation. Proposed learning outcomes for new process design courses include describing key relationships and directionality between product and process design functions, determining whether a component can be made with a process, selecting process sequences for products based on cost and/or environmental impact, specifying new process designs when needed, and choosing between product/process alternatives. Examples of instructional materials and approaches that are being developed to help meet these outcomes are discussed.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":"53 ","pages":"Pages 814-824"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54984311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-Material Topology Optimization Using Variable Density Lattice Structures for Additive Manufacturing","authors":"Vysakh Venugopal , Nathan Hertlein , Sam Anand","doi":"10.1016/j.promfg.2021.06.089","DOIUrl":"10.1016/j.promfg.2021.06.089","url":null,"abstract":"<div><p>Multi-material lattice structures are used in a range of load-bearing applications for multiple conditions including mechanical and thermal loads. Additive manufacturing processes with multi-material capabilities are well suited to manufacture multi-material structures. In this paper, a multi-material topology optimization approach has been presented using variable-density lattice structures where the geometry of the lattice structure is pre-defined. The objective of the proposed topology optimization method is to design lightweight parts with minimized compliance and thermal energy or improve the heat transfer capability. To facilitate that, a novel interpolation scheme based on the stiffness matrices of the lattice structures has been proposed. This interpolation scheme, unlike the traditional Solid Isotropic Material Penalization (SIMP) interpolation, is observed to perform better in terms of approximating the structure’s load-bearing capacity, primarily due to its formulation on the lattice’s stiffness matrices. This cubic Hermite spline-based interpolation scheme makes it amenable for gradient-based optimization methods. A sequential linear programming method has been used to solve the weighted multi-objective optimization model. A Pareto-frontier study has also been carried out to fully characterize the trade-offs between the two objectives – compliance minimization and thermal energy minimization.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":"53 ","pages":"Pages 327-337"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.06.089","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54984486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laura Talens Peiró , Francesco Baiguera , Andrea Maci , Marco Olivieri , Paola Villa , Marcello Colledani , Xavier Gabarrell i Durany
{"title":"Digitalization as an enabler of the Circular Economy of electronics","authors":"Laura Talens Peiró , Francesco Baiguera , Andrea Maci , Marco Olivieri , Paola Villa , Marcello Colledani , Xavier Gabarrell i Durany","doi":"10.1016/j.promfg.2021.07.010","DOIUrl":"10.1016/j.promfg.2021.07.010","url":null,"abstract":"<div><p>To facilitate the transition from a linear to a circular economy there is a need to develop digital tools that can provide comprehensive and useful data to enhance repair, remanufacturing, reuse, and recycling. This paper explains the typology of information key for such end, it discusses the current limitations and difficulties to implement methods in a digital platform, and a description of already existing digital solutions that will be further improved in the context of the DigiPrime project. A preliminary analysis of the availability and accessibility of information about electronics is required before the definition of a digital tool to support circular economy. First, the paper discusses the need of ‘digitalized’ end ‘standardized’ information of electronics to promote circular strategies. Then, diverse digitalization approaches by several teams of the Digiprime project are detailed. The paper concludes with a description of the next steps needed to align the diverse digitalization approaches and its potential contribution to improve the electronics sector.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":"54 ","pages":"Pages 58-63"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.07.010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54984786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
John Soldatos , Nikos Kefalakis , Angela-Maria Despotopoulou , Ulf Bodin , Andrea Musumeci , Antonella Scandura , Carlo Aliprandi , Dena Arabsolgar , Marcello Colledani
{"title":"A digital platform for cross-sector collaborative value networks in the circular economy","authors":"John Soldatos , Nikos Kefalakis , Angela-Maria Despotopoulou , Ulf Bodin , Andrea Musumeci , Antonella Scandura , Carlo Aliprandi , Dena Arabsolgar , Marcello Colledani","doi":"10.1016/j.promfg.2021.07.011","DOIUrl":"10.1016/j.promfg.2021.07.011","url":null,"abstract":"<div><p>In recent years there has been a growing interest in Circular Economy (CE), which promises to reduce waste and improve sustainability. The promise of CE is to change the conventional “take–make–dispose” that causes massive waste flows based on the integration of demanufacturing and remanufacturing processes within value chains. This integration requires breaking the ”silos” of the circular chain to establish new collaborative and sustainable value networks. The paper introduces a novel digital platform for the CE, which is currently under development in the H2020 DigiPrime project. The platform is destined to facilitate seamless and trusted information exchange across circular actors, while offering a range of value-added services that enable manufacturers, remanufactures, recyclers and other actors to gain insights in the status of recycling and waste management processes. The latter facilitates the implementation of zero waste processes, along with the assessment of the performance of the circular chain. The paper introduces the architecture of the digital platform, along with its data modelling, exchange and data traceability mechanisms. It also presents a CE use case used to validate the platform.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":"54 ","pages":"Pages 64-69"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.07.011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54984801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Global supply chain quality integration strategies and the case of the Boeing 787 Dreamliner development","authors":"Roland Schmuck","doi":"10.1016/j.promfg.2021.07.014","DOIUrl":"10.1016/j.promfg.2021.07.014","url":null,"abstract":"<div><p>Managing the quality of global supply chains is critical for the success of global companies. Quality disseminates through the supply chains. Supply chain quality integration facilitates each company to use its main expertise which can lead to higher quality and cost reductions. Digital audits enhance the possibilities to ensure the production quality at the suppliers. A global supply chain quality integration is illustrated through the case of the Boeing 787 Dreamliner development. The development process was a major challenge for Boeing because not only several innovations were introduced in the 787 plane, but the supply chain quality integration reached new levels for the company. The 787-program had process, management, labor, and demand risks. The first 787 plane was delivered three years later than planned and the budget was exceeded by 10 billion USD. To solve the issues, Boeing created the Production Integration Center. It sent engineers and production workers to its suppliers in several countries of the world to smooth the supply chain quality integration. Boeing supported its suppliers with its knowledge. Onsite cameras were used as digital audits. The Production Integration Center intervened when it estimated delays in the shipments. Boeing successfully solved the issues, but they cost the company a lot. Examining this supply chain restructuring case can help supply chain managers to diagnose and overcome issues in supply chain quality integrations.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":"54 ","pages":"Pages 88-94"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.07.014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54984838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design and additive manufacturing of a fatigue-critical aerospace part using topology optimization and L-PBF process","authors":"Akin Dagkolu , Istemihan Gokdag , Oguzhan Yilmaz","doi":"10.1016/j.promfg.2021.07.037","DOIUrl":"10.1016/j.promfg.2021.07.037","url":null,"abstract":"<div><p>Additive Manufacturing (AM) is a new generation manufacturing method and AM is using digital CAD data directed to the machine to manufacture. AM is therefore regarded as a direct digital manufacturing method. This research work presents the methodology for designing critical aerospace parts used under fatigue conditions for AM. Selected fatigue critical aerospace part was topologically optimized then re-designed for manufacturability. With this optimization study, 45 % mass saving was obtained while mechanical requirements were satisfied. Manufacturing simulations for thermal distortions are covered and the optimized part was manufactured with laser powder bed fusion (L-PBF) and secondary operations were applied.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":"54 ","pages":"Pages 238-243"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.07.037","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54985122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detection of exact and near duplicates in phased-array ultrasound weld scan","authors":"Etienne Provencal , Luc Laperrière","doi":"10.1016/j.promfg.2021.07.041","DOIUrl":"10.1016/j.promfg.2021.07.041","url":null,"abstract":"<div><p>Finding duplicates in phased-array ultrasound weld scans is typically done by certified analysts. Due to the vast amount of data involved, this task is time-consuming and error-prone. Some automated analysis software exists but are still inefficient. In this paper, two types of duplicates are defined. A method to detect each type in a database of three-dimensional ultrasound weld scans is presented. The duplicate detection process is implemented in a cloud-computing service enabling near real-time processing in industrial applications. Experiments are performed to expose the detection accuracy of both methods.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":"54 ","pages":"Pages 263-268"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.promfg.2021.07.041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54985181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jaakko Peltokorpi, Lauri Isojärvi, Kai Häkkinen, Esko Niemi
{"title":"QR code-based material flow monitoring in a subcontractor manufacturer network","authors":"Jaakko Peltokorpi, Lauri Isojärvi, Kai Häkkinen, Esko Niemi","doi":"10.1016/j.promfg.2021.10.016","DOIUrl":"10.1016/j.promfg.2021.10.016","url":null,"abstract":"<div><p>Principal manufacturers suffer from uncertainty as they lack up-to-date information on their orders in supply chains (SCs). The current era of digitalization offers many solutions to monitor order statuses through integrated information systems. However, the requirements to implement such systems are high for the companies and they still prefer personal interactions with suppliers. This paper proposes a QR code-based order monitoring system in a subcontractor manufacturer network. The objective of the study is to assess the technological and operative maturity of the system in real SCs. A prototype system was built and demonstrated to representatives from Finnish companies in a virtual workshop. The feasibility study showed that the QR code-based monitoring system is practical and promising. The companies, however, recognize that its implementation would be challenging from both the technical integration and subcontractor adaptation points of view. The results obtained give insights into modern information management in SCs and suggest areas of interest for further studies.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":"55 ","pages":"Pages 110-115"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2351978921002134/pdf?md5=cf1a01701091cd50dcc25009609b7f00&pid=1-s2.0-S2351978921002134-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54985532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Görick , L. Larsen , M. Engelschall , A. Schuster
{"title":"Quality Prediction of Continuous Ultrasonic Welded Seams of High-Performance Thermoplastic Composites by means of Artificial Intelligence","authors":"D. Görick , L. Larsen , M. Engelschall , A. Schuster","doi":"10.1016/j.promfg.2021.10.017","DOIUrl":"10.1016/j.promfg.2021.10.017","url":null,"abstract":"<div><p>Thermoplastic composites (TCs) are a famous choice when it comes to high performance designs for industrial applications. Since the growing demand on the use of this material, it is important to be able to evaluate suitable processing technologies. One of those technologies is continuous ultrasonic welding (CUSW) which creates continuous joints, also called seams, between two or more TCs parts. In CUSW mechanical oscillations are applied to the material and result in melting and connecting of the welding parts.</p><p>The approach to predict joint strength (qualities) of continuous ultrasonic welded TCs by training different neural networks is investigated in this study. Quality class prediction around 72 % accuracy is achieved with a fully connected neural network. Concluding, quality prediction of welded TCs with the help of artificial intelligence seems to be a suitable approach for quality observation but more research could lead to more reliable neural networks for industrial applications.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":"55 ","pages":"Pages 116-123"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2351978921002146/pdf?md5=40cac27e61437d063f733b91d0e4f424&pid=1-s2.0-S2351978921002146-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54985543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}