Review
Automation & Control Systems
Kamran Latif, Anbia Adam, Yusri Yusof, Aini Zuhra Abdul Kadir
Summary: CNC technology has been a significant pillar of manufacturing for decades, and various technologies have been introduced and developed worldwide in order to push for the development of next-generation manufacturing systems. The paper discusses major technologies such as CN, CAD, CAPP, CAM, G codes, STEP model data, STEP-NC, and OAC, with a focus on the development and implementation of STEP and STEP-NC technologies, as well as the role of OAC technology in CNC system development.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Nishant Ojal, Brian Giera, Kyle T. Devlugt, Adam W. Jaycox, Alexander Blum
Summary: This study proposes a novel method to transform digital definitions into unique tensor-like structures for complete regeneration of the original STEP file. The resulting STEP tensors enable easy part comparison and evaluation of part similarity based on specific geometry, material composition, and design intent.
JOURNAL OF INTELLIGENT MANUFACTURING
(2022)
Article
Engineering, Electrical & Electronic
Shafi Khurieshi Mohammed, Mathias Hauan Arbo, Lars Tingelstad
Summary: This article utilizes Product Manufacturing Information (PMI) from STEP AP242 neutral files to facilitate gripper selection and grasp planning in a robotic assembly operation. The PMI, along with part geometry and dimensions, is used to identify various handling features of the parts and select a suitable gripper. Two methods for adding PMI to the STEP files are discussed, one involving a custom string and the other using standard entities defined in the ISO 10303 AP242: 2020 standard. The entire process is demonstrated through a use case.
Article
Automation & Control Systems
S. Mukunthan, R. Manu, Deepak. K. Lawrence
Summary: This paper proposes a method to automate the tolerance analyses of mechanical assembly using ISO 10303 STEP AP242 files derived from 3-D CAD models, which has been verified through two case studies.
ASSEMBLY AUTOMATION
(2022)
Article
Automation & Control Systems
Jinhua Xiao, Benoit Eynard, Nabil Anwer, Alexandre Durupt, Julien Le Duigou, Christophe Danjou
Summary: This paper proposes a STEP/STEP-NC-compliant process data model to define specific application objects and entities in 3D printing, model manufacturing data relationships and constraints, and standardize process parameters.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Jumyung Um, Joungmin Park, Ian Anthony Stroud
Summary: This paper introduces an innovative method to address the limitations of inaccuracies and volumetric losses in additive manufacturing, showing the potential for applying the process to various metal industries.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Manufacturing
Kamran Latif, Yusri Yusof, Aini Zuhra Abdul Kadir, Renan Bonnard, Efrain Rodriguez, Nazareno de Oliveira Pacheco
Summary: The adoption of STEP-NC on CNC machines remains one of the most challenging issues in daily operations. This implementation focuses on improving the interpreted STEP-NC programming paradigm and introduces a new data interpretation approach and algorithm design. The system combines indirect and interpreted strategies and includes software tools and algorithms for data extraction, tool path development, and execution.
INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM
(2023)
Article
Engineering, Industrial
Ruben Moliner-Heredia, Ignacio Penarrocha-Alos, Jose Vicente Abellan-Nebot
Summary: This paper proposes a methodology to calibrate the Stream of Variation (SoV) model using data from inspection stations and prior engineering-based knowledge. The methodology involves a recursive algorithm that minimizes the difference between the sample covariance of the measured Key Product Characteristic (KPC) deviations and its estimation, resulting in an adjusted model.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Automation & Control Systems
Kang Cheng, Gang Zhao, Wei Wang, Yazui Liu
Summary: This study proposes an estimation methodology of energy consumption based on the STEP-NC program, which achieves the staged and overall estimation of energy consumption for parts by analyzing the influencing factors of energy consumption and establishing the mapping relationship between the STEP-NC program and the estimation method.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Fahad Ali Milaat, Paul Witherell, Martin Hardwick, Ho Yeung, Vincenzo Ferrero, Laetitia Monnier, Matthew Brown
Summary: This paper proposes an amended STEP-NC compliant data representation for powder bed fusion (PBF) in additive manufacturing (AM). The representation defines the characteristics of interlayer relationships and technology controls in PBF, and simulation results demonstrate the feasibility of granular process planning control. The contributions of this research highlight the importance of information models in AM, promoting data representations as key enablers of the AM technology and supporting the neutrality and interoperability of data across AM systems.
JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING
(2022)
Article
Green & Sustainable Science & Technology
Hyeon Park, Yesol Woo, Hyun Seung Jung, Gookhee Kim, Jong Wook Bae, Myung-June Park
Summary: This study analyzed two different syngas-to-DME processes using experimental data and kinetic models, finding that the single-reactor configuration significantly improved CO conversion and DME production rate compared to the two-reactor method. Recycling unreacted gas could more than double the carbon efficiency for both reactor configurations.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Automation & Control Systems
Abdelilah Elmesbahi, Irene Buj-Corral, Jihad El Mesbahi, Oussama Bensaid
Summary: This article introduces the STEP-NC standard and its application in computer-aided process planning (CAPP) for turning processes. By building an automatic manufacturing feature recognition (AMFR) module and a new consistent-fast algorithm, full communication between CAD and CAM is achieved, enabling machining to meet the needs of modern manufacturing.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Engineering, Industrial
Yu Zhang, Xian Yu, Jian Sun, Yongsheng Zhang, Xun Xu, Yadong Gong
Summary: This paper introduces an intelligent STEP-NC-compliant setup planning method that combines rules, AHP, and IBPNN, to automatically and reasonably optimize the machining sequence and datum decision of manufacturing feature groups. The proposed method is verified to be effective and feasible through a case study.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Engineering, Manufacturing
Shafi Khurieshi Mohammed, Mathias Hauan Arbo, Lars Tingelstad
Summary: This article proposes the use of GD&T information from STEP AP242 for robotic manufacturing applications. Two methods are discussed for including GD&T using the STEP AP242 Edition 2 neutral file exchange format. A novel process of extracting and interpreting relevant PMI for robotic manufacturing applications is described. Various applications of this information for robotic manufacturing are discussed through two use-cases.
INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM
(2023)
Article
Computer Science, Artificial Intelligence
Seyedehtina Zaringhalam, Mohammad Khalilzadeh, Omid Fatahi Valilai
Summary: With increasing competition in manufacturing industries, it is necessary for firms to enhance the design of new products to facilitate quick and collaborative interaction among stakeholders. The proposed framework for a cloud collaborative manufacturing system uses the STEP standard to ensure data integrity and enables stakeholders to work collaboratively and interactively. The framework also supports the integration of stakeholders in the design and production stages.
PEERJ COMPUTER SCIENCE
(2023)
Review
Engineering, Industrial
Chao Liu, Pai Zheng, Xun Xu
Summary: This paper presents a systematic literature review on the digitalisation and servitisation of machine tools in the context of Industry 4.0. The review provides a comprehensive understanding of recent advancements in this field, including key technologies, methods, standards, architectures, and applications. Additionally, a novel conceptual framework called Cyber-Physical Machine Tool (CPMT) is proposed as a systematic approach to achieving digitalisation and servitisation of next-generation machine tools. The paper also discusses major research issues, challenges, and future research directions.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Qiunan Meng, Xun Xu
Summary: In this paper, an incomplete covering rough set method based on object similarity is proposed to derive a cover for attribute reduction. Experimental results show that it outperforms compared rough set in factor selection accuracy and quote prediction with various proportions of missing data.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Zhenyang Gao, Guoying Dong, Yunlong Tang, Yaoyao Fiona Zhao
Summary: This article proposes a machine learning aided design method to generate conformal cooling systems that match the thickness distribution of the part, solving the temperature variance issue. By optimizing the design parameters, the proposed method achieves better temperature control and lower coolant pressure drop compared to conventional designs.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Review
Computer Science, Artificial Intelligence
Ying Zhang, Mutahar Safdar, Jiarui Xie, Jinghao Li, Manuel Sage, Yaoyao Fiona Zhao
Summary: This article reviews recent publications on the application of machine learning in additive manufacturing, focusing on data types, data handling methods, and implemented ML algorithms. Examples of ML applications in AM are categorized based on lifecycle stages and research focuses. Existing public databases and data management methods are introduced, and the limitations of current data processing methods are discussed, along with suggestions for future perspectives.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Review
Automation & Control Systems
Jiarui Xie, Manuel Sage, Yaoyao Fiona Zhao
Summary: The progress of machine learning has provided new opportunities for gas turbine modelling. Feature selection and feature learning techniques are important for addressing the challenges in this field. This review paper examines 46 studies that utilized FSFL techniques for GT modelling, and provides a categorization framework and implementation recommendations.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Editorial Material
Engineering, Industrial
Pai Zheng, Xun Xu, Lihui Wang
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Yaoyao Ping, Yongkui Liu, Lin Zhang, Lihui Wang, Xun Xu
Summary: Cloud manufacturing is a manufacturing model that provides on-demand manufacturing services to consumers. Scheduling is a crucial problem for cloud manufacturing, especially when dealing with multiple composite tasks. This research combines sequence generation algorithms with deep reinforcement learning to address cloud manufacturing scheduling problems.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Yongkui Liu, Yaoyao Ping, Lin Zhang, Lihui Wang, Xun Xu
Summary: Cloud manufacturing is a service-oriented manufacturing model that provides manufacturing resources as cloud services. This paper explores the use of Deep Reinforcement Learning (DRL) to solve scheduling issues in decentralized robot manufacturing services in cloud manufacturing, proposing DQN and DDQN-based scheduling algorithms. Results indicate that DDQN performs the best in terms of performance and indicators.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Law
Marwan Gharbia, Alice Chang-Richards, Xun Xu, Matilda Hook, Lars Stehn, Rene Jahne, Daniel Hall, Kenneth Park, Jingke Hong, Yingbin Feng
Summary: Through surveys conducted in several countries, this study found that self-certification by manufacturers is the main method of complying with building regulations when using off-site construction techniques. A regulatory compliance system that allocates risks and liabilities fairly is also important. Third-party certification and traceability are necessary for a functional regulatory system. The study recommends policymakers introduce changes in product standards and legislation to improve off-site construction's compliance and performance.
JOURNAL OF LEGAL AFFAIRS AND DISPUTE RESOLUTION IN ENGINEERING AND CONSTRUCTION
(2023)
Article
Energy & Fuels
Camilo Carrillo, Eloy Diaz Dorado, Jose Cidras Pidre, Julio Garrido Campos, Diego San Facundo Lopez, Luiz A. Lisboa Cardoso, Cristina I. Martinez Castaneda, Jose F. Sanchez Rua
Summary: This paper presents a methodology that utilizes electrical measurements to detect the state of a sheet-metal-forming press and identify the produced parts, production pace, and energy demand. The analysis is conducted at the press subsystem level and relies on neural networks to estimate press states and identify parts. The proposed methodology provides accurate estimation of the produced parts and valuable information for evaluating press energy performance.
Article
Automation & Control Systems
Chonghui Zhang, Jiarui Xie, Ali Shanian, Mitch Kibsey, Yaoyao Fiona Zhao
Summary: This paper proposes a hybrid design framework that combines the advantages of both DL forward design and inverse design based on the mixture density network (MDN). The framework can generate designs with designated mechanical properties at less than 10% relative errors at a lower computational cost.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Engineering, Industrial
Pei Wang, Hai Qu, Qianle Zhang, Xun Xu, Sheng Yang
Summary: In this paper, a production quality prediction framework based on multi-task joint deep learning is proposed to simultaneously evaluate the multitask quality of all stages in a multistage manufacturing system. The proposed method outperforms traditional models in terms of R2, MAE, and RMSE, showing significant improvements in quality prediction accuracy.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Industrial
Ahmed Z. Naser, Fantahun Defersha, Xun Xu, Sheng Yang
Summary: This paper explores the feasibility of predictive Life Cycle Assessment (LCA) for Additive Manufacturing (AM) by proposing a data-driven framework that combines Machine Learning (ML) and LCA. The framework is demonstrated through a case study on the Fused Filament Fabrication (FFF) process, achieving high prediction accuracy and good generalizability.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Industrial
Kendrik Yan Hong Lim, Theresia Stefanny Yosal, Chun-Hsien Chen, Pai Zheng, Lihui Wang, Xun Xu
Summary: The increasing complexity of industrial systems requires more effective and intelligent maintenance approaches to address manufacturing defects. This paper introduces a cognitive digital twin system that leverages industrial knowledge graphs to support maintenance planning and operations. The system can manage interconnected systems, facilitate cross-domain analysis, and generate feasible solutions validated through simulation. It can also identify potential disruptions in new product designs.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Shuo Su, Aydin Nassehi, Ben Hicks, Joel Ross
Summary: This paper proposes a comprehensive characteristic, called identicality, for digital twins in the manufacturing domain, to evaluate their capability of representing their physical counterparts. The characteristic includes completeness, trueness, precision, and latency. The evaluation method involves manufacturing scenario analysis and identicality evaluation.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
