Manufacturing Capabilities Research Articles

Holistic evaluation of involute gear surfaces using 3D point cloud inversion

Gear users desire increased performance from their products and are interested in predicting the behavior (vibration, loss, service life, etc), and gear manufacturers are interested in adjusting machining parameters to manufacture even better gears. Both require proficient metrology. The evaluation standards were originally written to classify the manufacturing capability of machine tools and as tolerances tighten they may not provide enough insight into the functional performance of the manufactured parts. Furthermore, the advantage of modern coordinate and gear measuring machines is not fully taken into account when applying standardized measurement and evaluation strategies. Improved analysis tools can increase the relevant information gained from current measurement capabilities and enable more useful functional characteristics to be specified by designers and manufacturers. A key improvement is to move from profile and helix line traces to flank surfaces and corresponding fitted form elements. This is achieved by the introduced method. We present an inversion algorithm that fits dimension, form, and pose, and is applicable with current methods through freezing of specific fitting parameters. The method fits a synthetic point cloud with output results that are accurate to the 7th digit, or in practical terms are numerically equal. The inversion method can increase the understanding of error contributions and the functional performance of gears.

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Plasma electrolytic polishing of additively manufactured metal parts: Optimizing the post processing workflow

Additive manufacturing of metal parts is gaining acceptance in industry due to its unique manufacturing capabilities. Higher surface roughness of printed parts is one of the major challenges of this advanced manufacturing technique, which requires a crucial post-processing stage before the components can be used in practice. This study investigates the influence of plasma electrolytic polishing (PeP) and the combination of PeP and particle blasting as a post processing technique for additively manufactured stainless steel samples. The results show a 70% improvement in surface roughness after 10 minutes of particle blasting and 3 minutes of PeP in sequence and presents the possibility of optimizing processing time to achieve better surface qualities with minimal post processing time.

Artificial Intelligence at Work: Transforming Industries and Redefining the Workforce Landscape

Global industry transformation is occurring due to the adoption of Artificial Intelligence (AI) in the workplace, bringing a new era of productivity, creativity, and revolutionary change. AI technologies are evolving into essential tools that improve workflows, automate repetitive operations, and enhance human capabilities in various industries, including finance, human resources, and manufacturing. AI-driven robotic systems in manufacturing improve speed and precision, boosting output and economy of scale. Artificial intelligence (AI) algorithms that analyze large datasets and provide insights into market patterns, risk, and investing strategies benefit the financial sector. AI-powered chatbots are revolutionizing customer care by offering prompt, customized support. This article explores the multifaceted impact of Artificial Intelligence (AI) on the contemporary workforce, briefly examining its transformative influence on various industries.

3D printing in aerospace and defense: A review of technological breakthroughs and applications

The integration of 3D printing technology in the aerospace and defense sectors has heralded a paradigm shift in manufacturing processes, design capabilities, and operational efficiency. This review explores the transformative impact of 3D printing on these industries, focusing on breakthroughs and applications that have reshaped traditional methodologies. Technological advancements in additive manufacturing have facilitated the production of complex geometries and intricate components that were once deemed impractical or impossible. Aerospace engineers and defense manufacturers are now leveraging 3D printing to create lightweight, high-strength structures, optimizing the balance between performance and fuel efficiency. This has led to enhanced aircraft design and functionality, as well as the development of unmanned aerial vehicles with unprecedented capabilities. Moreover, the ability to rapidly prototype and iterate designs has significantly reduced the time-to-market for new aerospace and defense systems. The review delves into case studies showcasing how 3D printing has streamlined the development process, enabling quicker adaptation to evolving threats and technological advancements. In the defense sector, the customization potential of 3D printing has revolutionized the production of weapons and equipment. Tailoring components to specific mission requirements enhances the effectiveness of military operations while reducing costs associated with mass production. The review also highlights the role of 3D printing in the development of advanced sensors, communication devices, and protective gear for defense personnel. However, challenges such as material limitations, standardization, and certification processes persist. The review provides insights into ongoing research and development efforts addressing these challenges, aiming to further unlock the full potential of 3D printing in aerospace and defense. This review offers a comprehensive overview of the current state of 3D printing in aerospace and defense, emphasizing its transformative impact on manufacturing, design, and operational capabilities. As the technology continues to evolve, its integration is poised to shape the future landscape of these critical industries.

A novel vision-based multi-functional sensor for normality and position measurements in precise robotic manufacturing

Cobots play an essential role in the fourth industrial revolution and the automation of complex manufacturing processes. However, cobots still face challenges in achieving high precision, which obstructs their usage in precise applications such as the aerospace industry. Nonetheless, advances in perception systems unlock new cobot manufacturing capabilities. This paper presents a novel multi-functional sensor that combines visual and tactile feedback using a single optical sensor, featuring a moving gate mechanism. This work also marks the first integration of Vision-Based Tactile Sensing (VBTS) into a robotic machining end-effector. The sensor provides vision-based tactile perception capabilities for precise normality control and exteroceptive perception for robot localization and positioning. Its performance is experimentally demonstrated in a precise robotic deburring application, where the sensor achieves the high-precision requirements of the aerospace industry with a mean normality error of 0.13° and a mean positioning error of 0.2 mm. These results open a new paradigm for using vision-based sensing for precise robotic manufacturing, which surpasses conventional approaches in terms of precision, weight, size, and cost-effectiveness.

Optimization of product design process in cloud manufacturing system based on swarm intelligence

ABSTRACT Currently, manufacturing industries in many countries are grappling with an imbalance in the supply and demand of manufacturing resources, encompassing resource scarcity and idleness, as well as insufficient and surplus manufacturing capabilities. To address this issue, cloud manufacturing has emerged, integrating the Internet of Things, cloud computing, and advanced manufacturing technologies. This fusion enables the on-demand allocation of manufacturing resources and capabilities, facilitating efficient networked production. However, in the realm of the Internet, the challenge lies in efficiently aligning abundant information with a company’s manufacturing objectives to genuinely deliver an “on-demand service.” This represents a pivotal issue that demands immediate resolution within the operational framework of cloud manufacturing platforms. To effectively address the optimization challenge in Manufacturing Cloud Services (MCS), this study leverages two dimensions: the fundamental Quality of Service (QoS) of MCSs and the interrelated QoS among these services. A holistic QoS model for assembling MCSs is constructed. In this model, the timely relevance of fundamental QoS data is ensured through the incorporation of a temporal weighting function, while an enhancement in the precision of optimization is achieved by considering the interconnections between service combinations. The final simulation experiments showcase the effectiveness of the proposed approach in this paper.

Development of electron optical capabilities for manufacturing of large components by electron beam welding

Electron beam welding (EBW) is a fast process that shows promise to be used for high-productivity welding of thick-section components in the nuclear industry. Nuclear AMRC has been working for many years on developing the use of EBW for small modular reactor (SMR) applications, such as joining thick-section pressure vessel components. The major strength of EB is the single-pass process that can radically reduce fabrication times. This is also one of the major issues with EB. The stress on the welding operator is high as any error generally means failure. In chamber EB operation, such as the Pro-beam K2000 system at Nuclear AMRC, once the chamber is closed, the only interaction between the operator and the work piece is through a camera or the electron beam. Tracking features of the material or the joint line is important to gather as much information on the situation as possible. Nuclear AMRC has used the functions of the Pro-beam multimode to gain reliability during welding. The seam tracker relies on electron optical image analysis to assess the deviation of the beam from the joint line, but it is the duty of the operator to assess whether the correction should be applied. The team has demonstrated that based on the results of the seam tracker, more work is necessary before welding. It was also demonstrated that the seam tracker can be further used to align the beam/gun to the joint and assess variations in a gap in the joint or a variation of working distance for further process reliability.

Prediction modeling of cigarette ventilation rate based on genetic algorithm backpropagation (GABP) neural network

AbstractThe ventilation rate of cigarettes is an important indicator that affects the internal quality of cigarettes. When producing cigarettes, the unit may experience unstable ventilation rates, which can lead to a decrease in cigarette quality and pose certain risks to smokers. By establishing the ventilation rate prediction model, guide the design of unit parameters in advance, to achieve the goal of stabilizing unit ventilation rate, improve the stability of cigarette ventilation rate, and enhance the quality of cigarettes. This paper used multiple linear regression networks (MLR), backpropagation neural networks (BPNN), and genetic algorithm-optimized backpropagation (GABP) to construct a model for the prediction of cigarette ventilation rate. The model results indicated that the total ventilation rate was significantly positively correlated with weight (P < 0.01), circumference, hardness, filter air permeability, and open resistance. The results showed that the MLR models' (RMSE = 0.652, R2 = 0.841) and the BPNN models’ (RMSE = 0.640, R2 = 0.847) prediction ability were limited. Optimization by genetic algorithm, GABP models were generated and exhibited a little better prediction performance (RMSE = 0.606, R2 = 0.873). The results indicated that the GABP model has the highest accuracy in the prediction of predicting ventilation rate and can accurately predict cigarette ventilation rate. This method can provide theoretical guidance and technical support for the stability study of the ventilation rate of the unit, improve the design and manufacturing capabilities and product quality of short cigarette products, and help to improve the quality of cigarettes.

A novel thermal bus architecture for large cryogenic space telescopes utilizing helium pulsating heat pipes

Future space telescopes, such as those proposed for the Far-infrared Surveyor Mission, are expected to employ actively cooled optical arrays with a similar overall surface area compared to the James Webb Space Telescope. Therefore, there is a need for a cryogenic cooling system with a thermal bus architecture that can distribute cooling to these large optical arrays. Recent experimental research of helium Pulsating Heat Pipes (PHPs) has shown that helium PHPs can transfer heat over long distances (on the order of 2 m) with high efficiency, and also have the ability to act as a passive thermal switch upon the removal of the cooling source. PHPs’ high thermal performance, passive switching capability, low mass, and ease of manufacturing make them an appealing option compared to high-purity metal straps for a thermal bus architecture on large cryogenic space telescopes. A novel architecture for the thermal control of optical arrays is proposed utilizing unique configurations of helium pulsating heat pipes that minimize mass, maximize thermal performance, and reduce the risk of mission failure.

Optimising Offset Defence Implementation as Fulfilment Efforts in Fighters Aircraft Materials and Technology

This research aims to investigate the implementation of defense offset as a strategy to address the gap in the supply of materials and technology for fighter aircraft among countries. In this context, the gap arises due to the complexity and high costs associated with fighter aircraft development. Many countries, particularly those with limited technological and manufacturing capabilities, face challenges in acquiring and developing advanced aircraft. This gap negatively impacts their defense capability enhancement efforts. Therefore, the concept of defense offset emerges as a potential solution. Defense offset is a strategy in which foreign aircraft manufacturers provide compensation in the form of technology transfer, investment in the local defense industry, or research and development collaboration to the purchasing country. Through steps such as identifying material and technological needs, planning clear offset agreements, transferring relevant technology, developing the local industry, supplying materials, research and development collaboration, as well as monitoring and evaluation, the implementation of defense offset can be optimized. This research employs a qualitative method with a descriptive approach, involving a literature study to gain in-depth information about defense offset implementation and its impact on the material and technology gap in fighter aircraft. The results include the identification of factors influencing the success of defense offset implementation, political, economic, and strategic implications, as well as the benefits obtained by purchasing countries. In conclusion, through the optimization of defense offset, purchasing countries can reduce the gap in materials and technology for fighter aircraft, enhance domestic defense industry, and strengthen national defense capabilities. With the right strategy, defense offset can be an effective tool in addressing the gap in fighter aircraft material and technology, thereby fortifying national defense.

Quantum-inspired computing technology in operations and logistics management

PurposeThe purpose of this paper is to explore and disseminate knowledge about quantum-inspired computing technology's potential to solve complex challenges faced by the operational agility capability in Industry 4.0 manufacturing and logistics operations.Design/methodology/approachA multi-case study approach is used to determine the impact of quantum-inspired computing technology in manufacturing and logistics processes from the supplier perspective. A literature review provides the basis for a framework to identify a set of flexibility and agility operational capabilities enabled by Industry 4.0 Information and Digital Technologies. The use cases are analyzed in depth, first individually and then jointly.FindingsStudy results suggest that quantum-inspired computing technology has the potential to harness and boost companies' operational flexibility to enhance operational agility in manufacturing and logistics operations management, particularly in the Industry 4.0 context. An exploratory model is proposed to explain the relationships between quantum-inspired computing technology and the deployment of operational agility capabilities.Originality/valueThis is study explores the use of quantum-inspired computing technology in Industry 4.0 operations management and contributes to understanding its potential to enable operational agility capability in manufacturing and logistics operations.

Artificial Intelligence in the Industrial Engineering

The integration of Artificial Intelligence (AI) into industrial engineering, epitomized by the advent of Industry 4.0, has reshaped manufacturing landscapes. This article explores the profound impact of AI over the past decade, focusing on predictive maintenance, operational optimization, robotics, quality control, and supply chain management. Predictive maintenance, facilitated by machine learning algorithms, minimizes downtime and optimizes resource allocation. Operational optimization, achieved through AI's real-time data analysis, enhances decision-making, resource utilization, and overall efficiency. The infusion of AI into robotics elevates manufacturing capabilities, while quality control processes benefit from advanced image recognition and machine learning, ensuring higher standards. In supply chain management, AI predicts demand, optimizes inventory, and streamlines routes, fostering resilience. Human-machine collaboration, highlighted by collaborative robots and AI-driven workforce empowerment, underlines the transformative synergy. The article concludes with a reflection on the past decade's developments, emphasizing the ongoing evolution of AI in industrial engineering, promising smarter, more adaptable, and globally competitive operations in the future.

How Global Collaboration Can Improve the Medical Countermeasure Life Cycle for Infectious Disease Outbreaks.

Infectious disease outbreaks have become increasingly common and require global partnership for adequate preparedness and response. During outbreaks, medical countermeasures (MCMs)-vaccines, therapeutics, and diagnostics-need to reach patients quickly. Recent outbreaks exemplify that products with regulatory approval can expand access and reach patients quicker than investigational products. Unfortunately, insufficient funding globally and differences in funders' prioritization puts gains and future efforts at risk. Of primary concern is (1) lack of a feasible regulatory path and clinical capability to achieve regulatory approval for new MCMs for many diseases; and (2) the need for partners with the mandate, funding, and capabilities to support long-term sustainment of manufacturing capability and stockpiling of licensed products. Without collaboration, the global community runs the risk of losing the capabilities built through years of investment and being underprepared to combat future threats. Synergies between funders are critical to create long-term sustainment of products to ensure access.

The Role of FDI in India's Manufacturing Sector: Growth, Challenges, and Opportunities

This research paper explores the pivotal role of Foreign Direct Investment (FDI) in the growth and transformation of India's manufacturing sector, with a focus on recent trends, challenges, and future opportunities. It highlights the positive impact of FDI facilitated by government policies, including the "Make in India" initiative, which aims to boost the country's manufacturing capabilities and position it as a global hub. The study underscores the significant contributions of FDI to enhancing production capacity, technological advancements, and job creation. However, it also identifies key challenges, such as regulatory hurdles and inadequate infrastructure, that continue to limit the sector's full potential. In the context of recent global economic shifts, including the impacts of the COVID-19 pandemic and evolving trade policies, the paper examines how these factors influence FDI inflows and the strategic positioning of India's manufacturing industry. According to recent data from the Reserve Bank of India, FDI inflows into the manufacturing sector increased by 15% in the fiscal year 2021-2022, reflecting the sector's resilience and continued attractiveness.1 The paper concludes with recommendations for policy reforms aimed at creating a more conducive environment for FDI, essential for the sustained growth and competitiveness of India's manufacturing sector.

Exploring the Academic–Industry Collaboration in Knowledge Sharing for Supplier Selection: Digitalizing the OEM

Increasing reliance on digital technologies has led to a significant shift in how businesses operate, with many now relying heavily on digital platforms for effective planning, communication, sales, marketing, supply chain, and logistics management. In this context, knowledge sharing platforms enable academic–industry collaboration in which exchange of ideas, opinions, experience, and expertise brings collective intelligence in cooperative learning ecosystem thereby expediting decision making. However, establishing long-term commitment among the partners, allocation of time and resources for sharing tacit knowledge, collaboration among partners with different strategic priorities, and real-time knowledge sharing capabilities are essential for effective and rapid learning in knowledge sharing platforms. The present article will examine these benefits and challenges in knowledge sharing and its impact on supplier selection platforms in Asian automakers. The findings of this article will be helpful for researchers and practitioners intending to explore the role of cooperation in knowledge sharing and digital transformation amid competitive environment prevalent in the automotive industry. The potential supplier database is first examined for qualifying the capability requirements put forth in this article and further prioritized using a multicriteria decision-making technique and analytic hierarchy process. The article results reveal that the manufacturer has highly prioritized firms’ financial transparency for supplier evaluation followed by the suppliers’ cost control, quality control, and manufacturing capabilities. The article has significant theoretical and practical implications for developing robust supplier evaluation criteria for automobile industry and a digital ecosystem for original equipment manufacturers in making supplier related decisions.

Material extrusion-based additive manufacturing with multi-legged robot: fundamental investigation of path planning and manufacturing capabilities

Material extrusion-based additive manufacturing with multi-legged robot: fundamental investigation of path planning and manufacturing capabilities

Exploring the Nexus: IT Capabilities, Digital Transformation, and Innovation in Traditional Manufacturing

This research investigates the interplay between information technology capabilities, digital transformation strategies, and digital innovation performance in traditional manufacturing enterprises. Utilizing a multi-case exploratory research approach, incorporating dynamic capability theory and institutional theory, hypotheses were formulated and validated through empirical analysis of questionnaire survey data. Findings reveal that IT capabilities positively influence both digital product and process innovation performance. Additionally, digital transformation strategies mediate the relationship between IT capabilities and innovation performance. Organizational legitimacy moderates the impact of digital transformation strategies on innovation performance, while environmental dynamism influences the relationship between IT capabilities, transformation strategies, and innovation performance. The study underscores the importance of aligning internal resources with strategic needs to navigate digitalization successfully in traditional manufacturing contexts.

The Current Design for Additive Manufacturing Research Frontier

Design for additive manufacturing (DFAM) seeks to develop designs that take advantage of the unique capabilities of additive manufacturing (AM) processes to maximize benefits. In this paper, several issues at the frontier of DFAM research are highlighted. First, the need is described to include as-manufactured mechanical and other physical properties, such as topology and shape optimization and generative design, during computational design. AM processes rarely produce parts with homogeneous composition and isotropic properties, so design methods and tools should not assume them. Second, the topic of designing for the AM process chain is important since AM-fabricated parts typically need postprocessing operations, such as support removal, finish machining, heat treatments, etc. DFAM methods need to incorporate the entire process chain, not just the AM process, which is explored with an example from metal powder bed fusion. Third, potentially, the largest benefit of AM can be realized by radically rethinking product architectures. Examples of an electric motorcycle and an assistive exosuit illustrate the ideas and potential benefits. Finally, some thoughts on design for 4D printing are offered, specifically for 3D printed morphing and deployable systems that utilize the shape memory effect.

A Proposed Hybrid Model for Cost Management of Agility Smart Supply Chains Using Nanotechnology- Case Study

Purpose – The purpose of this paper is to present a proposed hybrid model for managing the cost of agility smart supply chains using Nanotechnology. Methodology – The paper concentrates on a case study of the Egyptian Electric Cables company related to the new implementation of Nanotechnology in Egypt’s industrial sector. The data was collected through interviews with company officials specializing in Nanotechnology since 2022. The paper constructs a model for managing the cost of an agile smart supply chain using the Fuzzy Model. The methodology involves defining specific capabilities and attributes, establishing linguistic scales for performance evaluation, and computing fuzzy performance indices. These indices aim to quantify the performance of agile attributes and capabilities within the context of Nanotechnology’s application in smart supply chains, culminating in an overall Fuzzy Performance Index. Findings – The Egyptian Electric Cables company’s utilization of Nanotechnology within their agile smart supply chain demonstrates remarkable effectiveness, as indicated by the fuzzy performance index values. Their success appears in adeptly managing various factors: flexibility, allowing adaptability to market demands and diverse product ranges; responsiveness, ensuring strong supplier relationships and swift adjustments to market fluctuations; competence, exhibited through effective collaboration, product quality, and skilled workforce development; cost management, focusing on controlling expenses throughout the sourcing, manufacturing, and delivery processes; and performance, emphasizing efficiency, increased output, and resource optimization. These practical results prove the company’s success in integrating Nanotechnology to efficiently manage costs within its agile smart supply chain model. Originality – It is believed that there is no study to date examining the effect of using Nanotechnology on the cost management of agility smart supply chains. This paper contributes to the limited literature on Nanotechnology and cost management of agility smart supply chain. It develops a fuzzy model that integrates Nanotechnology within the scope of capabilities (Flexibility, Responsiveness, Competence, Cost, and performance) in sourcing, manufacturing, and delivery within the agile smart supply chain, the construction of this fuzzy model was guided by the researchers’ creation of the suggested hybrid model for agile smart supply chains, integrating Nanotechnology and leveraging advanced technologies. Keywords: Nanotechnology, Cost Management, Nano Supply Chains, Agility Supply Chains, Smart Supply Chains, Value Chains, RFID, 3D printing.