Design for additive manufacturing (DFAM) provides design freedom creating complex geometries and guides designers to ensure the manufacturability of parts fabricated using (AM) processes. However, there is a lack formalized DFAM knowledge that information on how plan AM processes achieving target goals. Furthermore, wide variety processes, materials, machines creates challenges in determining constraints. Therefore, this study presents ontology web language (OWL) semantically model retrieve...

This research aims to develop a set of new formal design representations that captures requirements improve the level personalisation while taking advantage additive manufacturing (AM)-enabled freedom. We propose process structure called for AM-facilitated merges and manufacturing. Also, we an artefact–user interaction using finite state automata goal-oriented user behaviours in artefact use as language sets based on discrete event systems. By adopting relational properties affordance,...

Additive manufacturing (AM) assisted by a digital twin is expected to revolutionize the realization of high-value and high-complexity functional parts on global scale. Machine learning (ML) introduced in digitized AM provides potential transform data into knowledge continuously automatically; hence products will be designed manufactured with improved quality. Conventional product development systems, however, fail fully adopt ML algorithms increasingly available for acquisition. To address...

Abstract Real-time monitoring for Additive Manufacturing (AM) processes can greatly benefit from spatial-temporal modeling using deep learning. However, existing, deep-learning approaches in AM are case-dependent, and therefore not robust to changes of control inputs data types. As is dynamic complex, this limitation leads a lack systematic, DL real-time AM, which involves large number varying parameters data. To address the challenge, paper introduces novel approach developing models...

Abstract Metal powder bed fusion additive manufacturing (AM) processes have gained widespread adoption for the ability to produce complex geometries with high performance. However, a multitude of factors still affect build process, which significantly impacts rate. This, in turn, leads great challenges achieving consistent and reliable part quality. To address this challenge, simulations measurements been progressively deployed provide valuable insights into quality individual builds. This...

Design for additive manufacturing (DFAM) provides design freedom creating complex geometries and guides designers to ensure manufacturability of parts fabricated using (AM) processes. However, there is a lack formalized DFAM knowledge that information on how plan AM processes achieving target goals, e.g., reducing build-time. Therefore, this study presents ontology the web language (OWL) formalize support queries retrieving knowledge. The has three high level classes represent rules...

Abstract Additive manufacturing (AM) for metals is rapidly transitioning to an accepted production technology, which has led increasing demands data analysis and software tools. The performance of laser-based powder bed fusion (PBF-LB/M), a common metal AM process, depends on the accuracy analysis. Advances in acquisition are being propelled by increase new types situ sensors ex measurement devices. Measurements taken with these devices volume, variety, value PBF-LB/M but decrease veracity...

Abstract Metal, powder-bed-fusion-based, additive manufacturing (AM) processes have gained widespread adoption for the ability to produce complex geometries with high performance. However, a multitude of factors still affect build process, which significantly impacts rate. This, in turn, leads great challenges achieving consistent and reliable part quality. To address this challenge, simulations measurements been progressively deployed provide valuable insights into quality individual...

Many industries, including manufacturing, are adopting data analytics (DA) in making decisions to improve quality, cost, and on-time delivery. In recent years, more research development efforts have applied DA additive manufacturing (AM) decision-making problems such as part design process planning. Though there many AM problems, not all benefit greatly from DA. This may be due insufficient data, unreliable or the fact that is cost effective when it some problems. paper proposes a framework...

In this digital era, the natures of services are becoming increasingly complex and diverse due to convergences between existing human-centered other supportive device services, or interactions heterogeneous services. Expecting trend is be accelerated more, new scientific engineered approaches service design needed more than ever. context, a designed conceptually abstractly has significant limitations that keep customers’ satisfaction from advancing above certain level. Hence, in an initial...

Abstract Background Dementia is a major public health problem affecting millions of people worldwide. Early diagnosis and intervention are essential to improve quality life reduce the burden dementia. Recently, voice digital biomarkers have emerged as promising approach for early detection dementia owing its clinical utility accessibility. Method In this study, we present biomarker‐based prediction system using Korean dataset from AI hub entitled cognitive disorder diagnostic...

Manufacturing and service sectors are evolving towards achieving a design of systemically integrated product-service system (PSS). While there exist limitations, we propose an integrative architecture method for PSSs. For the architecture, our study adopts concepts functions affordances as fundamentals PSS designs to achieve both product life-cycle related specifications. Also, finite state automata is applied modeling add computations into method. discussions on automotive shows method's...

Abstract Selective laser melting (SLM) is modernizing the production of highly complex metal parts across manufacturing industry. However, achieving material homogeneity and controlling thermal deformation remain major challenges for metal-based, additive manufacturing. Therefore, adequate control systems are needed to monitor build processes, ensure part quality throughout production. Traditionally, designs relied on physics-based knowledge in analyzing, characterizing, modeling complex,...

Additive Manufacturing (AM)’s advance from rapid prototyping to the end-of-use products inevitably challenges conventional design theories and methodologies. Especially while adopting systematic engineering methodologies for AM (DfAM), it is essential develop new methods that explore space enabled by AM’s freedom early stage. To address challenge, this study provides a framework method modeling AM-enabled product behaviors in conceptual phase of DfAM. Firstly, contrasts function-based with...