Shohin Aheleroff- PhD
- Researcher at University of Auckland
Shohin Aheleroff
- PhD
- Researcher at University of Auckland
Guest Editor, Machines | Review Editor, Frontiers Journal
About
16
Publications
32,140
Reads
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1,332
Citations
Introduction
Shohin is passionate about mass personalization. He obtained a Ph.D. and has been honored with the University of Auckland Distinguished Graduate Award. With over two decades of industrial experience in global companies, he has delivered a wide range of smart solutions as a program manager.
Current institution
Education
March 2017 - March 2020
The university of Auckland
Field of study
- Mass Personalisation by utilizing 4.0 technologies and capabilities
Publications
Publications (16)
There is a recognized need for mass personalization for sustainability at scale. Mass personalization is becoming a leading research trend in the latest Industrial Revolution, whereas substantial research has been undertaken on the role of Industry 4.0 enabling technologies. The world is moving beyond mass customization, while manufacturing has led...
![Generic system architecture for CPMT. Adopted from [7].](publication/365518559/figure/fig1/AS:11431281213182432@1702964546827/Generic-system-architecture-for-CPMT-Adopted-from-7_Q320.jpg)
Smart factory development renders an incredible opportunity for the manufacturing industry to join the Fourth Industrial Revolution (Industry 4.0). However, an incredible number of conventional CNC machine tools are populating the world’s factories. Replacing these machines is an expensive process. This task might be considered unliftable by most s...
In today's competitive market, mass personalisation has become a recognised necessity. However, ensuring data privacy and security while addressing the global cybersecurity challenge is crucial. While previous studies focused on meeting individual requirements, the emerging business opportunity of mass personalisation necessitates collaboration and...
We have entered an era of personalisation at scale, but product lifecycle has not developed adequately to achieve highest customer satisfaction. Review literature in a wide range of business and industries shows that mass production cannot fulfil the market demand. This paper investigates the degree of mass personalisation (DoMP) based on the criti...
Machine learning technologies have recently emerged as transformative tools for enhancing project management accuracy and efficiency. This study introduces a data-driven model that leverages the hybrid eXtreme Gradient Boosting-Simulated Annealing (XGBoost-SA) algorithm to predict the time and cost of construction projects. By accounting for the co...
The Fourth Industrial Revolution (Industry 4.0) leads to mass personalisation as an emerging manufacturing
paradigm. Mass personalisation focuses on uniquely made products to individuals at scale. Global challenges
encourage mass personalisation manufacturing with efficiency competitive to mass production. Driven by
individualisation as a trend and...
Recent findings have shown that Digital Twin served multiple constituencies. However, the dilemma between the scope and scale needs a sophisticated reference architecture, a right set of technologies, and a suitable business model. Most studies in the Digital Twin field have only focused on manufacturing and proposed explicit frameworks and archite...
The Fourth Industrial Revolution (Industry 4.0) leads to an age of extraordinary changes through digital transformation. High customer demands and market competitions drive almost all business sectors to meet individuals’ requirements with a cost close to mass production. This paper aims to get the best out of Digital Twin capabilities for meeting...
Mass personalization has been an essential paradigm in the Industry 4.0 era. Mass personalization has long been a question of great interest in a wide range of industries. There is a recognized need for a cost-effective approach for dealing with a high number of unique products and services. There has been substantial research undertaken on the rol...
Manufacturers expect the extra value of Industry 4.0 as the world is experiencing digital transformation. Studies have proved the potential of the Internet of Things (IoT) for reducing cost, improving efficiency, quality, and achieving data-oriented predictive maintenance services. Collecting a wide range of real-time data from products and the env...
Acquiring and retaining the most profitable customers is a big concern of a telecommunication operator to perform more targeted marketing therefore business demand and competition between mobile operators is becoming more based on life cycle of customers in the network. In order to improve customer satisfaction and fulfill requirements, several dat...
Competition between the mobile operators is becoming more based on subscriber's behavior. In order to improve mobile operator's competitiveness and customer value, several data mining technologies can be used. One of the most important data mining technologies is customer clustering and segmentation. This targeting practice has been proven manageab...
Questions
Questions (16)
Industry 5.0 aims to shift from the technology-centered focus of Industry 4.0 to a more human-centered approach. What are the key factors and strategies needed to successfully implement this transition, particularly in enhancing human-machine collaboration and sustainable production?
The concept of Industry 5.0 is neither widely established nor well-developed and implemented. Therefore, there would likely be discussions concerning the fundamental Industry 4.0 enabling technologies within the context of the Industry 5.0 era.
- Hard Milling Process Based on Compressed Cold Air-Cooling Using Vortex Tube for Sustainable and Smart Manufacturing
- Digitising a Machine Tool for Smart Factories
- A Hybrid Fuzzy Multi-Criteria Decision-Making Model for Evaluating the Influence of Industry 4.0 Technologies on Manufacturing Strategies
Digital Twin, simulation, and modeling seem related concepts but have distinct differences. What do you think?
To what extent is Google Maps a Digital Twin of the transportation system?
Industry 5.0 represents the next phase of the industrial revolution, emphasizing human-machine collaboration, personalized production, and sustainability. This discussion aims to assess the world's readiness for embracing Industry 5.0 goals.
Considering the potential benefits of Industry 5.0, understanding the world's readiness for Industry 5.0 is essential as we transition into the next industrial revolution.
Do you consider 3D printing/ Additive manufacturing for personalized products at scale?
Do you consider DM, DS, DT, and DP to be classifications of Digital Twins?
