Energy management effectively reduces energy consumption, improves material utilisation, minimises emissions and maximises product output during manufacturing. Thus, enterprises are implementing an energy management strategy and improving sustainable competitive advantage. With the rapid development of the Internet of Things, Cyber-Physical Systems and Big Data, sustainable smart manufacturing provides

ABSTRACT The aim of this study has been to develop a two-level multi-objective genetic algorithm (MOGA) to optimize risk-based LCC analysis to find the optimal maintenance replacement time for road tunnel ventilation fans. Level 1 uses a MOGA based on a financial risk model to provide different risk percentages, while level 2 uses a MOGA based on an LCC model to estimate the optimal fan replacement

The selection process for the best computer-aided manufacturing (CAM) software among a set of potential number of alternatives in market has been critical issue for most companies that aim to make their design/manufacturing-related activities automated. Because this selection process is very vital for companies because a wrong decision might put them into a difficult position in terms of economical

(2020). Special issue on ‘transdisciplinary approaches to digital manufacturing for industry 4.0’. International Journal of Computer Integrated Manufacturing: Vol. 33, Transdisciplinary approaches to digital manufacturing for Industry 4.0, pp. 321-324.

Digital twin models are computerized clones of physical assets or systems and have attracted much attention from academia and industries. Digital twin applications focus on smart manufacturing systems. Meanwhile, manufacturing products are driven increasingly by the needs of customers. Industrial production modes have evolved from mass production to personalized production. Understanding customers

Future manufacturing systems such as Industry 4.0, Cloud Manufacturing, or Cyber-Manufacturing System (CMS) rely on the seamless integration of cyber and physical domains in the manufacturing systems. However, this increased connectivity within a factory and between factories enlarges the attack surface for malicious individuals. Potential intrusions – especially cyber-physical attacks – can cause

A novel method for geometric model reconstruction of a damaged blade is presented to improve the precision machining of aero-engine blade repair. Based on the theoretical model of the blade, the iterative closest point (ICP) algorithm is used to determine the relationship between the measuring points and the theoretical model. Blade deformation mechanisms are analyzed to construct the fitting function

One of the main challenges within collaborative business ecosystems are the management of Interoperability. Indeed, Interoperability is a crucial prerequisite that must be satisfied when enterprises need to work together for seizing new business opportunities and improving competitiveness. To develop and improve enterprise systems interoperability, a set of interoperability requirements needs to be

This paper investigates the applicability of two computational intelligence methods for the plasma cutting process modelling: artificial neural networks and adaptive neuro-fuzzy inference systems. After exploring the possibilities of neural networks learning from the experimental data for the prediction of the plasma cutting parameter, the adaptive neuro-fuzzy inference system approach was used in

ABSTRACT With the integration of new-generation information and communication technology (ICT) in the manufacturing industry, many advanced manufacturing modes have been proposed. Cloud manufacturing (CMfg) is one example which integrates manufacturing resources and the provision of on-demand services using new technologies, such as Internet of Things (IoT), Big Data and cloud computing. CMfg has experienced

Developing the mathematical optimization models for multi-pass and multi-stage machining processes, due to their mathematical and implicational complexity is important. Despite extensive research on the optimization of machining processes by considering different assumptions, few studies have been conducted on the processes in which the tool passes over the workpiece surface several times at different

Any shortage and deviation in the implementation of logistics processes can lead to a poor performance and losing the market share of the manufacturer. To overcome this problem, the identification of existing risks in all logistics sub-processes, and taking corrective/preventive measures, is of great importance. In this study, a risk prioritization approach is presented based on a sequential multi-stage

ABSTRACT Digital Twin (DT) implementations can contribute to smart manufacturing by integrating the physical and the cyber space. Artificial Intelligence (AI) applications based on Machine Learning (ML) are widely accepted as promising technologies in manufacturing. However, ML methods require large volumes of quality training datasets and in the case of supervised ML, manual input is usually required

A new electronic seeding device was designed for large-sized seeds, such as soybean, corn, and peanuts, that supports an independent electronic-controlled seeding process. The developed seeding device consists of a programmable logic controller, pulse generator, stepper motor, and stepper motor driver. Based on the Box–Behnken Design model, the effects of different factors on the plant spacing control

The paper deals with the problem of placing objects coming from an input transportation system – conveyor belt – on a specific position of another output moving transportation system and with time and velocity synchronization. The paper focuses on the case of the synchronous and precise placing of objects without predefined patterns of shapes and when they have unknown mechanical properties or when

The presented study seeks to identify the role of crowdsourcing within the scope of Industry 4.0. For this purpose, a Systematic Literature Review was performed, starting from 476 articles that mentioned “crowdsourcing’ and ‘Industry 4.0’, which were reduced to 31 articles that comprised the corpus of the review work after exclusion filters were applied. These articles brought factors related to the

With the development of digital twin, the research on the fusion of intelligent manufacturing system and digital twin technology attracts more attention. In this paper, the realization of digital twin is studied for geometric feature online inspection system of body-in-white (BIW). A three-level virtual modeling approach of Element-Behavior-Rule is proposed for the physical environment modeling in

To compensate the joint torque of Axis-II caused by end loading and mass of links in industrial robots, static balancing mechanisms are generally used. There are several existing balancing mechanism techniques. However, as these techniques lack autonomy, continuity and dynamics, they cannot completely compensate the joint torque in the presence of dynamic or multiple types of loads. In this paper,

The Whale Optimization Algorithm (WOA), which mimics the social behavior of humpback whales, is a recently developed meta-heuristic algorithm. However, WOA exists the defect of easily falling into local optimum. This paper proposes a new WOA based on a self-adapting parameter adjustment and a mix mutation strategy (abbreviated as SMWOA). The self-adapting parameter adjustment strategy based on a normal

The advancement of technology and the empowerment of the industry have made humans and robots more closely tied together, known as human-robot collaboration. A sector that specifically utilises this collaboration is the printed circuit boards industry. Therefore in this industry, proper allocation of tasks to humans and robots is crucial. This study investigates this type of allocation to minimise

Aim to solve all kinds of problem existing in the angle grinder assembly line of the enterprise, such as the unreasonable distribution of work procedures, serious work in progress (WIP) inventory, chaotic production line layout and low assembly line balancing. Value Stream Map (VSM) is used to describe the layout and process diagram of the assembly line and a future value flow chart is established

This paper investigates the five-axis continuous machining strategy on cost-effective five-axis CNC milling systems, which is limited by simultaneous control of any four axes at a given time. The proposed strategy consists of (1) generation of five-axis continuous milling tool path for conventional five-axis machines using a CAD/CAM software, and (2) conversion of the generated tool path to four-axis

Process planning for sheet metal bending involves the determination of a near-optimal bend sequence for a given part. The problem is complex since the search space of possible solutions is factorial with respect to the number of bends. In this paper, a two-stage algorithm is described that allows for the quick identification of a near-optimal bend sequence for a given part and set of tools. In the

Accurate prediction of the deviations/deformations is highly necessary for the new product development process. It is a tedious multi-tasking activity, in which various aspects need to be considered in the early phase of design. This paper proposes a new constitutive and collaborative framework to model the functional assembly geometry. For complex industrial applications in the multi-plant scenario

In semiconductor manufacturing systems, a time-constrained multi-cluster tool should be scheduled such that a wafer stays in a process chamber in a given time range to satisfy a wafer residency time constraint. In practice, activity time is subject to variation. It could lead to some fluctuation of wafer residency time in a process chamber. Hence, it is crucial to analyze how wafer residency time varies

The occurrence of mine quake is subject to coupling control of multiple factors. To study the influence of mine quake distribution on rock burst under different incentive conditions, based on massive microseismic monitoring data, this paper established time-varying signal analysis model for deep recurrent neural network and restricted Boltzmann machine deep process neural network, which supports multi-perspective

In this paper, an algorithm model is proposed to describe the emotion regulation process of human beings based on Hidden Markov Model (HMM). The process of reappraisal strategy in emotion regulation is optimized by an individual’s personality and the effect of interaction between emotions. Firstly, the theoretical bases in this paper, the theory of Gross emotion regulation process and the Five-Factor

The digital twin-based manufacturing system is a typical representative of smart manufacturing and has a number of advantages beyond the state of the art. However, when a manufacturing system needs to be reconfigured to meet new requirements of production, manual reconfiguration is time-consuming and high labor cost because of the complexity of the digital twin-based manufacturing system and the imperfection

With the arrival of the Fourth Industrial Revolution, also known as Industry 4.0, there is a need to deploy digital projects that have a dependency relationship with legacy systems in acquiring and managing information making it more accessible to the user. In addition, this integration needs to be synchronized with other countries so as not to lead to uneven maturity among organizations, leading to

Technological and scientific advances set out the expanding of new opportunities for intelligent industries. The concept of Industry 4.0 is observed by expert groups as an important industrial configuration approach, however, much is still under discussion, especially in the emerging countries. There is a lack of practical studies and procedures on the implementation of this concept in companies. This

Traditional civil aircraft manufacturing enterprises are experiencing transformation from providing products to providing the civil aircraft services based on the entire life cycle. In the process of transformation and upgrading, a well-developed knowledge management system is crucial to support the rapid and agile development of enterprises, fast delivery of orders and increase in brand awareness

(2019). Correction. International Journal of Computer Integrated Manufacturing. Ahead of Print.

With the advent of Industry 4.0, design of a smart product to work in a smart factory, or at home or city over its lifecycle has to consider its intelligent interaction with its external environment (physical, human and cyberspace environments). Thus, environment interaction-driven design of smart products becomes an important design research field, facing a huge challenge of integrating a smart product

This paper reports on the development of Factory Optima, a web-based system that allows manufacturing process engineers to compose, optimise and perform trade-off analysis of manufacturing and contract service networks based on a reusable repository of performance models. Performance models formally describe process feasibility constraints and metrics of interest, such as cost, throughput and CO 2

Production-line sensors are essential for synchronisation and execution of the correct workflow in a manufacturing process. Usually, sensor faults lead to serious delays, or even the complete termination of the manufacturing process, to carry out maintenance. Thus, sensor faults compromise the reliability of the manufacturing system and disturb the production schedule. This study proposes a multiple-sensor

Current mass individualisation and service-oriented paradigm calls for high flexibility and agility in the warehouse system to adapt changes in products. This paper proposes a novel digital twin-driven joint optimisation approach for warehousing in large-scale automated high-rise warehouse product-service system. A Digital Twin System is developed to aggregate real-time data from physical warehouse

Manufacturing companies are striving for more environment-friendly operations and products, creating an increased need for a balance between environment friendliness and efficiency gains. This can be done by integrating and implementing lean and green practices simultaneously. To attain this objective, this paper presents a green-modified value stream mapping model, which uses carbon efficiency and

In product design, accuracy of the product information greatly affects design quality. The Taguchi method simplifies the analysis method and provides an effective product design approach by confirming the variable characteristics and determining the optimum combination of characteristics. However, determination of the levels of the variable characteristics in the Taguchi method relies on human experience

Transdisciplinarity is characterising numerous research areas, in which natural sciences are integrated with technical and social sciences, requiring mixed methodologies for achieving full sustainability. However, there is a lack of engineering methods and design tools able to effectively integrate the analysis of human performance and social impacts with technical issues during product and process

Cloud manufacturing is a promising rising paradigm in which geographically distributed manufacturing resources are exposed as services in the cloud platform. The task of cloud manufacturing is to provide manufacturing resources as services to fulfil users’ demands. However, in existing cloud manufacturing architecture all the information is possessed by the platform operator, and the management of

Kansei Engineering (KE) is a user-oriented technology combing customer psychological feelings and engineering for designing and developing products. Conventionally, questionnaire surveys have been extensively applied for understanding customers’ affective demands, responses and evaluations. However, the questionnaire is usually time-consuming, labour-intensive and small in data size. Online customer

As one of the most important components of machine tool, guideway has an important driving force to comprehensively improve the remanufacturability of machine tools. To select optimal guideway for machine tool remanufacturing, an integrated multi-criteria decision-making (MCDM) approach that combines improved analytic hierarchy process (AHP) and connection degree-based technique of ranking preferences

Customer satisfaction in purchasing new products is an important issue that needs to be addressed in today’s competitive markets. A product with good affective design excites consumer emotional feelings to buy the product. Affective design often involves complex and multi-dimensional problems for modelling and maximising affective satisfaction of customers. Machine learning is commonly used to model