Towards smart manufacturing: Implementation and benefits

international conference data science, 2019

Thanks to the rapid development and applications of advanced technologies, we are experiencing the fourth industrial revolution, or Industry 4.0, which is a revolution towards smart manufacturing. The wide use of cyber physical systems and Internet of Things leads to the era of Big Data in industrial manufacturing. Artificial Intelligence algorithms emerge as powerful analytics tools to process and analyze the Big Data. These advanced technologies result in the introduction of a new concept in the Industry 4.0: the smart Factory. In order to fully understand this new concept in the context of the Industry 4.0, this paper provides a survey on the key components of a smart factory and the link between them, including the Industrial Internet of Things, Big Data and Artificial Intelligence. Several studies and techniques that are used to enable smart manufacturing are reviewed. Finally, we discuss some perspectives for further researches.

2021

Due to the technological advancement in Today’s manufacturing systems, a large amount of data is generated in different volume, velocity, and variety of kinds. Extracting information from these data and make a real-time decision is a big challenge to the current manufacturing systems. This study presents a novel model that converts the iFactory learning facility into a fully Industry 4.0 (I4.0) manufacturing system. To achieve this purpose, we utilized the cyber physical system (CPS) components and sensors, the Internet of Things (IoT), deep learning methods, and cloud computing to fully meet the I4.0 enablers. Cloud computing is utilised in two phases: (1) during the model training phase to hold a large amount of product image data collected from the inspection station, and (2) during the execution of the model. The core learning model is based on a convolutional neural network (CNN) that is trained from the captured product images in the production line to predict the defective it...

Sustainable Futures, 2020

Smart manufacturing is the technology utilizing the interconnected machines and tools for improving manufacturing performance and optimizing the energy and workforce required by the implementation of bigdata processing, artificial intelligence and advanced robotics technology and interconnectivity of them. This paper defines and discusses the smart manufacturing system and states it current implementation status and analyzes the gap between current manufacturing system and the predicted future smart manufacturing system, discusses the technologies associated with it and their contribution in smart manufacturing technology. Also, to realize this rapidly growing technology and cover its all dimensions a survey of the latest developments in this field and its impacts were analyzed and presented along with the challenges of implementation, opportunities and the future directions for smart manufacturing system.

Asian Science Bulletin, 2024

The integration of all the processes that smart factories will use will take time, as they are very different from the norm. Among these procedures is: Machine learning: Every aspect of manufacturing is optimized, cutting time to market and energy usage, as systems acquire and evaluate fresh data. Over the past few decades, the growing trend of intelligent technology in industries such as manufacturing has drawn extensive study attention from all around the world. Numerous cutting-edge technologies are included in Smart Technology (ST), including blockchain, cyber-physical production systems, the Industrial Network of Things (IOT), internet of things, artificial intelligence and systematic data analysis. In order to reduce the distance between humans and machines, we give an overview of several smart technologies that can be used to regulate the sophisticated characteristics associated with computers and sensor technologies. This research paper shows the complete literature review of ST to increase the production and maintenance of machinery equipment and future threats faced by ST. This paper also includes a survey report on the rate of adoption today as compared to the past five years, to obtain real-time results, costeffective techniques and the use of different sensors to reduce the human workload in the manufacturing sector.

Sustainability

Adaptation and innovation are extremely important to the manufacturing industry. This development should lead to sustainable manufacturing using new technologies. To promote sustainability, smart production requires global perspectives of smart production application technology. In this regard, thanks to intensive research efforts in the field of artificial intelligence (AI), a number of AI-based techniques, such as machine learning, have already been established in the industry to achieve sustainable manufacturing. Thus, the aim of the present research was to analyze, systematically, the scientific literature relating to the application of artificial intelligence and machine learning (ML) in industry. In fact, with the introduction of the Industry 4.0, artificial intelligence and machine learning are considered the driving force of smart factory revolution. The purpose of this review was to classify the literature, including publication year, authors, scientific sector, country, in...

Acta Scientific Pharmaceutical Sciences, 2020

The start of a new decade brings a new wave of technological change and unprecedented opportunities that will generate massive amounts of data at the level of Big Data (BD), spawn new threats and transform the way we do business. Dealing with such enormous data structurally or unstructured-wise and process it in real-time requires a new innovative technology such as Artificial Intelligence (AI). Today, AI is capable of learning from its experience through the element of its Machine Learning (ML) in conjunction with the Deep Learning (DL) component and using them to adjust to new input and perform human-like performance, or at least to complement and enhance human abilities. Because of this capability, it encompasses every aspect of the enterprise in the years to come. That is why we believe AI, Automation, and Analytics are central to the success of the enterprise and encompass critical business areas, including data, business processes, the workforce, and risk and reputation.

—We are entering a new era of computing technology that many are calling the Internet of Things (IoT).Machine to machine, machine to infrastructure, machine to environment, the Internet of Everything, the Internet of Intelligent Things, intelligent systems–call it what you want, but it's happening, and its potential is huge. We see the IoT as billions of smart, connected " things " (a sort of " universal global neural network " in the cloud) that will encompass every aspect of our lives, and its foundation is the intelligence that embedded processing provides. The IoT is comprised of smart machines interacting and communicating with other machines, objects, environments and infrastructures. As a result, huge volumes of data are being generated, and that data is being processed into useful actions that can " command and control " things to make our lives much easier and saferand to reduce our impact on the environment. The creativity of this new era is boundless, with amazing potential to improve our lives.

International Journal of Production Research , 2018

Manufacturing has evolved and become more automated, computerised and complex. In this paper, the origin, current status and the future developments in manufacturing are disused. Smart manufacturing is an emerging form of production integrating manufacturing assets of today and tomorrow with sensors, computing platforms, communication technology , control, simulation, data intensive modelling and predictive engineering. It utilises the concepts of cyber-physical systems spearheaded by the internet of things, cloud computing, service-oriented computing, artificial intelligence and data science. Once implemented, these concepts and technologies would make smart manufacturing the hallmark of the next industrial revolution. The essence of smart manufacturing is captured in six pillars, manufacturing technology and processes, materials, data, predictive engineering, sustainability and resource sharing and networking. Material handling and supply chains have been an integral part of manufacturing. The anticipated developments in material handling and transportation and their integration with manufacturing driven by sustainability, shared services and service quality and are outlined. The future trends in smart manufacturing are captured in ten conjectures ranging from manufacturing digitisation and material-product-process phenomenon to enterprise dichotomy and standardisation.

2019

Production monitoring in real-time is a very important problem in smart manufacturing. It helps enterprises to timely detect abnormalities in the production process and then guarantee the product quality and reduce waste. In this paper, we develop a novel method to monitor the real-time production based on the Convolution Neural Network and the Support Vector Data Description algorithm. The numerical result shows that our proposed method leads to high efficient on the testing data.

Nature, 2017

scientific, social and political implications of largesse p.31 ENERGY Vaclav Smil's vast survey of the history of power, updated p.29 NEUROSCIENCE Who was the radical who gave his name to Parkinson's disease? p.28 REFUGEES Capitalism alone cannot reform the broken system p.26 Yet smart manufacturing can make industry more efficient, profitable and sustainable. Minimizing the distances over which products and components are transported reduces costs -financial and environmental. Computer modelling can identify risks and pinch points. It can, for example, anticipate impacts from deliveries delayed by extreme weather, a situation that affect the electronics industry after Thailand's major floods in 2011. Similarly, defects in printed electronics circuits 1 . But big data is a long way from transforming manufacturing. Leading industries -computing, energy and aircraft and semiconductor manufacturing -face data gaps. Most companies do not know what to do with the data they have, let alone how to interpret them to improve their processes and products. Businesses compete and usually operate in isolation. They lack software and modelling systems to analyse data. anufacturing is getting smart. Companies are increasingly using sensors and wireless technologies to capture data at all stages of a product's life. These range from material properties and the temperatures and vibrations of equipment to the logistics of supply chains and customer details. Truck engines beam back data on speed, fuel consumption and oil temperature to manufacturers and fleet operators. Optical scanners are used to spot Study and model industrial processes to save money, energy and materials, urges Andrew Kusiak. Robotic arms work on a Porsche body frame.