Manufacturing Paradigm Research Articles

A generic tri-model-based approach for product-level digital twin development in a smart manufacturing environment

Abstract Smart manufacturing, as an emerging manufacturing paradigm, leverages massive in-context data from manufacturing systems for intelligent decision makings. In such context, Cyber-Physical Systems (CPS) play a key role in digitizing manufacturing systems and integrating multiple systems together for collaborative works. Amongst different levels of smartness and connectedness of CPS, Digital Twin (DT), as an exact digital copy of a physical object or system including its properties and relationship with the environment, has a significant impact on realizing smart manufacturing. A DT constantly synchronizes with its physical system and provides real-time high-fidelity simulations of the system and offers ubiquitous control over the system. Despite its great advantages, few works have been discussed about DT reference models, let alone a generic manner to establish it for smart manufacturing. Aiming to fill the gap, this research introduces a generic CPS system architecture for DT establishment in smart manufacturing with a novel tri-model-based approach (i.e. digital model, computational model and graph-based model) for product-level DT development. The tri-model works concurrently to simulate real-world physical behaviour and characteristics of the digital model. To validate the proposed architecture and approach, a case study of an open source 3D printer DT establishment is further conducted. Conclusions and future works are also highlighted to provide insightful knowledge to both academia and industries at last.

Developing augmented reality capabilities for industry 4.0 small enterprises: Lessons learnt from a content authoring case study

Augmented reality (AR) has been proposed as a disruptive and enabling technology within the Industry 4.0 manufacturing paradigm. The complexity of the AR content creation process results in an inability for Small Enterprise (SE) to create bespoke, flexible AR training support “in-house” and is a potential barrier to industrial adoption of AR. Presently, AR content creation requires a range of specialist knowledge (e.g. 3D modelling, interface design, programming and spatial tracking) and may involve infrastructure changes (e.g. fiducial markers, cameras) and disruption to workflow. The research reported in this paper concerns the development and deployment of an Augmented Repair Training Application (ARTA); a template-based interface to support end user (shop floor) AR content creation. The proposed methodology and implementation are discussed and evaluated in a real-world industrial case study in collaboration with a Small Enterprise (SE) in the Used and Waste Electronic and Electrical Equipment sector (UEEE/WEEE). The need for end user friendly templates is presented in the conclusion alongside further related work.

Analysis of the Machining Process of Titanium Ti6Al-4V Parts Manufactured by Wire Arc Additive Manufacturing (WAAM).

In the current days, the new range of machine tools allows the production of titanium alloy parts for the aeronautical sector through additive technologies. The quality of the materials produced is being studied extensively by the research community. This new manufacturing paradigm also opens important challenges such as the definition and analysis of the optimal strategies for finishing-oriented machining in this type of part. Researchers in both materials and manufacturing processes are making numerous advances in this field. This article discusses the analysis of the production and subsequent machining in the quality of TI6Al4V produced by Wire Arc Additive Manufacturing (WAAM), more specifically Plasma Arc Welding (PAW). The promising results observed make it a viable alternative to traditional manufacturing methods.

Towards Zero-Warehousing Smart Manufacturing from Zero-Inventory Just-In-Time production

Over the past half-century, manufacturers have strived to achieve “Zero Inventory (ZI)” manufacturing, which puts the burden on suppliers to build their warehouses nearby production lines to meet the strict time delivery requirements of ZI production. Considerable improvements in manufacturing processes have been made. However, this practice in the meanwhile brings excessive warehousing operations along the supply chain. Recently, massive up-front investment has been made by some larger manufacturers for industrial 4.0 and warehouse automation to facilitate warehousing operations, such as put away and picking. However, warehouse operation activities enhanced by automation are still non-value-adding and current practice of redundant handling process implies continuous cost increase with the demand expanding. Therefore, it is of significance to simplify the corresponding operations as much as possible. This paper makes a comprehensive introduction to a new manufacturing paradigm named Zero-Warehousing Smart Manufacturing (ZWSM) from the concept, practices, principles, and core technologies. ZWSM basically aims to avoid traditional non-value-adding warehousing operations such as put away and order picking, as well as to reduce the warehousing space for operations to the minimum. First, prototype layout and basic practices under ZWSM are proposed. Second, synchronization, unitization and uncertainty hedging, which are the key principles to achieve the ZWSM, are explicitly introduced. Third, A Zero-Warehousing Smart Manufacturing Platform (ZWSMP) is developed with the Internet of Things (IoT) enabled infrastructures. Corresponding logistics services are presented to provide information visibility and achieve operations improvement. A case study of the Hong Kong prefabrication construction project is used to demonstrate the materials delivery process among different supply chain partners to provide a basis for zero-warehousing achievement.

A Hybrid Data-Based and Model-Based Approach to Process Monitoring and Control in Sheet Metal Forming

The ability to predict and control the outcome of the sheet metal forming process demands holistic knowledge of the product/process parameter influences and their contribution in shaping the output product quality. Recent improvements in the ability to harvest in-line production data and the increased capability to understand complex process behaviour through computer simulations open up the possibility for new approaches to monitor and control production process performance and output product quality. This research presents an overview of the common process monitoring and control approaches while highlighting their limitations in handling the dynamics of the sheet metal forming process. The current paper envisions the need for a collaborative monitoring and control system for enhancing production process performance. Such a system must incorporate comprehensive knowledge regarding process behaviour and parameter influences in addition to the current-system-state derived using in-line production data to function effectively. Accordingly, a framework for monitoring and control within automotive sheet metal forming is proposed. The framework addresses the current limitations through the use of real-time production data and reduced process models. Lastly, the significance of the presented framework in transitioning to the digital manufacturing paradigm is reflected upon.

A Study on Application of Generative Design System in Manufacturing Process

The paradigm of manufacturing is changing with the recent era of the fourth industrial revolution. In particular, with the rapid development of artificial intelligence technology, tremendous transformation is welcomed in various areas related to manufacturing. This study concentrated on the changes in manufacturing due to the development of a generative design system. It also analyzed how designers design products through a generative design system based on artificial intelligence. The changes in the design part of the manufacturing process through the creative design are as follows: First, once the designer sets up a rough conceptual design, and then enters the conceptual design into the generative design system, the computer provides with a basic form of design. After AI presents multiple designs, designers choose the appropriate and desirable one. Next artificial intelligence puts forward an optimal material proposal considering its function and economics. And the designer reviews this alternative. After the designer’s review, the computer comes up with a final proposal. Much of the design is done by artificial intelligence. This design method will be universal in the future. Therefore, this study analyzed the direction in which the generative design system would develop in the artificial intelligence era. And the results of this study are to present the theoretical basis of the future product design methodology.

Increasing structuration rate of 3D printable concretes: the effect of viscosity enhancing admixtures

Abstract In the last decades, 3D printing has emerged as a promising new paradigm for manufacturing. Even in the civil construction industry, it has gained attention from companies and researchers around the world. Despite of that, the properties of materials applied in the additive manufacturing process are still understudied. One of the challenges is the need to conciliate both high bearing capacity, sparing the need of any confining measures, and the ability of keeping fluidity for enough time, in order to avoid cold joints between the layers. In that scenario, viscosity enhancing admixtures (VEAs) can be a solution, because they are able of promoting flocculation, viscosity gain and yield strength increase, reducing the deposition time in between the layers, which may decrease the formation of cold joints. This research evaluated rheological parameters of four different VEAs and found out that they show potential for increasing the cohesion and buildability of concretes for 3D-printing. The results showed that this effect varies with the type and amount of the admixture adopted and bentonite clay, as a mineral powder material, performed best in comparison to other polymeric VEAs, presenting structuration rates of up to 62% higher than the reference mixture.

Availability of Manufacturing data resources in Digital Twin

Data and information are the basis of the integrated manufacturing environment. The latest, synonym of the integrated manufacturing environment is a digital twin. The concept of a digital twin has grown profoundly in recent years. Several models and frameworks are suggested to create a digital twin in manufacturing. Various information and data flows are involved in any manufacturing case. Diagnosis and gather required data and information is the first and basis of creating digital twin. Data ownership is a significant issue because of the large amount of isolated data islands and due to different data ownership relationships of the whole production chain. This study focuses on the ownership paradigm in manufacturing and digital twin. The reliable data resources in manufacturing the metal-based products are recognized. Available and unavailable data in the turning process are studied and classified in general form to cover every condition as a case study.

Potential Impacts of EU Circular Economy Policy on Manufacturing Paradigm

Potential Impacts of EU Circular Economy Policy on Manufacturing Paradigm

A Novel Truthful and Fair Resource Bidding Mechanism for Cloud Manufacturing

Cloud manufacturing is an emerging service-oriented and market-oriented networked manufacturing paradigm. Resource scheduling of cloud manufacturing is different from those of other manufacturing paradigms due to some distinctive characteristics, such as high concurrency of multi-service and multi-task, high heterogeneity and high dynamics of resources, incomplete information of cloud services and user-centric services. These characteristics make the resource scheduling problem of cloud manufacturing more complicated. Efficient resource scheduling and economic benefit are the major concerns of users in cloud manufacturing environment. A novel market-based continuous bidding mechanism is proposed in this paper by applying game theory. In this mechanism, the overall benefit of both the cloud service provider and the cloud service demander is considered as the optimization target. The constraints are the task delivery time and budget. For decomposable tasks, the constraints for each subtask are also considered in resource bidding. Service demanders can bid continuously until the corresponding service is obtained or the bidding constraint is violated. Experiments demonstrate the proposed resource bidding mechanism is efficient in cloud service scheduling and can ensure the cloud manufacturing market is truthful and fair.

Data-Driven Analysis for RFID-Enabled Smart Factory: A Case Study

The emergence of Internet of Things (IoT) and new manufacturing paradigms have brought greater complexity of massive datasets. Radio frequency identification (RFID), as one of the key IoT technologies, has been used to collect real-time production data to support the manufacturing decision-making in smart factories. The adoption of these technologies results in a large amount of data collection. To extract useful information from this data, this paper utilizes a big data approach to figure out useful insights from RFID-enabled data regarding possible bottlenecks or inefficiencies on the shop floor so as to improve the quality management. Time and quality are the main metrics measured in this paper, where the longest process times, part accuracy percentage, and failure rate are determined for each of the workers (UserIDs) and process types (ProcCodes). Key findings and observations are significant to make advanced decisions in the smart factory by making full use of the RFID captured data. Note to Practitioners — This paper was motivated by a real-life company which has used RFID technology for over ten years. Great myriad of data has been captured from frontline production shop floors where machines, workers, materials, and manufacturing jobs were logically associated. Processing time and quality data are studied in this paper so as to investigate the production performance in the RFID-enabled smart factory.

Fundamentals and new achievements in feature-based modeling, a review

Feature-based modeling approach has been widely utilized in various applications of product and process engineering. Initially, it was introduced for geometry representation in computer-aided design (CAD) utilities. With further developments in computer-aided engineering, process planning, and manufacturing, feature-based modeling gained higher importance and role for the integration of these systems. Despite considerable efforts to gain domain-neutral definition for features, they have been mostly defined for specific applications that restrict their reusability for different systems. Recent progress in the Internet of Things (IoT), Artificial Intelligence (AI), Big Data, in addition to additive and hybrid manufacturing techniques, has realized a new manufacturing paradigm called Social Manufacturing which needs significant cross-domain interactions and intensifies the demand for feature interoperability. In this paper, after presenting a brief history of the feature-based modeling approach and its development challenges, we focus on finding the approaches to tackle feature interoperability issues and investigate the role of features in Model-Based Definition (MBD) and the Social Manufacturing paradigm. Also, future research pathways to develop the feature-based modeling approach is presented.

An embedded machine vision system for an in-line quality check of assembly processes

In the context of the Industry 4.0 and Smart Manufacturing paradigm, this paper proposes a machine vision system for a flexible, precise and low-cost in-line geometric inspection of assembly processes. As a case study, the system has been targeted to the catalytic converter assembly process, in order to be easily integrated in the consolidated manufacturing flow. The system is based on developed algorithms to be applied on the image of the interfaces with the complete exhaust system the catalytic converter will be assembled into. An image segmentation procedure is described to robustly identify the region of interest (ROI) in the image. Afterwards, a geometrical model is proposed to detect any possible geometrical defects due to planar and/or rotational shifts of the interfaces around their expected positions. For the sake of validation, the proposed system has been implemented on a Raspberry Pi 3 Single Board Computer (SBC). It showed a sub-millimeter precision for planar movements and a maximum error in detecting the rotation angle lower than 1 degree, respectively. The modularity of the proposed approach makes it suitable to be realized also on different computational platforms, such as the modern heterogeneous System-on-Chips (SoC) hosting a general purpose microprocessor and a Field Programmable Gate Array (FPGA) on the same chip. Indeed, the most time-consuming computational steps can be efficiently realized on the FPGA, exploiting the parallel computing capability offered by a hardware implementation, thus accelerating the overall computation.

An Architecture for Easy Onboarding and Key Life-Cycle Management in Blockchain Applications

New manufacturing paradigms require a large number of business interactions between multiple cyber-physical systems with different owners. In this context, public distributed ledgers are disruptive because they make it possible to securely and publicly record proofs of agreements between parties that do not necessarily trust each other. Many industry leaders have already achieved significant business benefits using this technology, including greater transparency, improved traceability, enhanced security, increased transaction speed and costs reduction. While the benefits of blockchain technologies for industrial applications are unquestionable, these technologies have an inherent complexity that might be overwhelming for many users. To decrease entry barriers for industry users to distributed ledger technologies, it is necessary to have an easy user onboarding process and a simple key life-cycle management. In this paper, we propose an architecture that facilitates these processes and simplifies how users utilize decentralized applications without sacrificing on the expected security. To achieve this goal, our architecture uses a middleware that allows us to decouple the digital signatures required for paying blockchain fees from the ones required for authorization. This approach has the advantage that users are not forced to create wallets, buy cryptocurrency, or protect their private keys. For these reasons, our solution is a promising way of enabling a reasonable transition to the integration of distributed ledger technologies in industrial business processes.

An Operational approach to gauge the lean performance in bias tyre manufacturing: a case study

Tyre manufacturing firms are facing a host of challenges such as global competition, pricing strategies and complex production process. Due to the complexity of tyre manufacturing process, it is prone to waste which result in non-value added activities across the entire value stream. The study is undertaken in a bias tyre manufacturing firm which is based in the South India. The top management of the case firm is concerned about the increasing non-value added activities. The aim of the study is to devise a template to measure the leanness index of the bias tyre manufacturing firm. The proposed leanness template incorporates the eight types of wastes defined in lean manufacturing paradigm viz. overproduction, unnecessary inventory, waiting, transportation, processing, unnecessary motion, defects and underutilisation of human resource. This will facilitate the people at the operational level to take appropriate decisions. The results of the study indicate that the HR underutilisation and motion are most detrimental wastes in bias tyre manufacturing, which is due to the high rate of absenteeism among workers in all the three shifts.

An operational approach to gauge the lean performance in bias tyre manufacturing: a case study

Tyre manufacturing firms are facing a host of challenges such as global competition, pricing strategies and complex production process. Due to the complexity of tyre manufacturing process, it is prone to waste which result in non-value added activities across the entire value stream. The study is undertaken in a bias tyre manufacturing firm which is based in the South India. The top management of the case firm is concerned about the increasing non-value added activities. The aim of the study is to devise a template to measure the leanness index of the bias tyre manufacturing firm. The proposed leanness template incorporates the eight types of wastes defined in lean manufacturing paradigm viz. overproduction, unnecessary inventory, waiting, transportation, processing, unnecessary motion, defects and underutilisation of human resource. This will facilitate the people at the operational level to take appropriate decisions. The results of the study indicate that the HR underutilisation and motion are most detrimental wastes in bias tyre manufacturing, which is due to the high rate of absenteeism among workers in all the three shifts.

Tapered elasticæ as a route for axisymmetric morphing structures

Transforming flat two-dimensional (2D) sheets into three-dimensional (3D) structures by combining carefully made cuts with applied edge-loads has emerged as an exciting manufacturing paradigm in a range of applications from mechanical metamaterials to flexible electronics. In Kirigami, patterns of cuts are introduced that allow solid faces to rotate about each other, deforming in three dimensions whilst remaining planar. In other scenarios, however, the solid elements bend in one direction. In this paper, we model such bending deformations using the formulation of an elastic strip whose thickness and width are tapered (the 'tapered elastica'). We show how this framework can be exploited to design the tapering patterns required to create planar sheets that morph into desired axisymmetric 3D shapes under a combination of horizontal and vertical edge-loads. We exhibit this technique by recreating miniature structures with positive, negative, and variable apparent Gaussian curvatures. With sheets of constant thickness, the resulting morphed shapes may leave gaps between the deformed elements. However, by tapering the thickness of the sheet too, these gaps can be closed, creating tessellated three-dimensional structures. Our theoretical approaches are verified by both numerical simulations and physical experiments.

Social Manufacturing: What are its key fundamentals?

Abstract Product manufacturing activities must be synchronous with social, scientific and technological developments, social manufacturing as a kind of next generation manufacturing paradigm combines the state-of-the-art technologies, such as Internet, cyber physical system (CPS) and internet of things. This paper is a typical position paper for elaborating the key fundamentals of social manufacturing based on its characteristics. The theoretical research and empirical study on social manufacturing in recent years, six key fundamentals have emerged and can be summarized as demands on service principles, grouping and communities with complex network, extended CPS and nets for industrial needs, collective intelligence in social manufacturing, block chain for cyber-credits and matched industrial software framework and models. Demands on service principles is the base key fundamental and determine others. In this paper, the key fundamentals and the technologies behind them have been analyzed for better development of social manufacturing in the future.

Leagile manufacturing paradigm in the production of jet pump - an implementation experience

One of the types of pumps that find high demand from the customers is jet pumps. Today, pump manufacturing companies are required to produce conventionally designed jet pump as well as improved and innovative forms of the same to meet the demand of several customers. This kind of demand can be fulfilled only when leagile manufacturing paradigm is implemented around the production of jet pumps. In order to have a successful implementation of the same, while pursuing the research reported in this paper, a model named as 'pumping for leagility' (PFL) was designed and applied in the case of producing jet pumps in a typical Indian pump manufacturing company. The PFL model has eight steps comprising of 31 activities. By applying PFL model, the nuances of developing leagile manufacturing paradigm in real-time practice was examined and the extent of implementation in the production of jet pump was studied.

Performance measurement of India-based third party logistics sector: an empirical study of user versus provider perspectives

The global third-party logistics (3PL) market was valued at US $802 billion in 2016 and is projected to exceed US $1.1 trillion by 2022. It is becoming increasingly essential for the 3PL service providers’ and 3PL service users’ to adjust their future logistics strategies and operations to be part of a wider ecosystem featuring digital infrastructure involving Internet of Things (IoT), big data, localized systems of value creation, which is likely to result in a distributed manufacturing paradigm. To enable development of effective future logistics strategies, which deals with the challenges mentioned above – we collected data by conducting 600 structured interviews from 300 senior management, middle management and front-line managers based at 3PL Service Providers’, and 3PL Service Users’ via a matched-pair design. The respondents were located in India and had a PAN-India geographical and industrial coverage. We present an analysis of the current differences in the current capabilities and requirements of 3PL service providers’ and service users, and by assessing how these differences can be bridged, to develop the necessary capabilities of being able to respond to a distributed manufacturing paradigm environment, which is being driven by IoT and encompass smart city products and ‘hybrid’ technologies and products.