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A new system for on‐machine measurement of workpieces is described. The system is based on a fine touch sensor that enables the cutting tool itself to act as a contact probe to inspect the workpiece. The proposed measurement technology combines the Q‐setter with the fine touch sensor. This low cost measurement system is applied to automatic workpiece setup and improving workpiece dimensional accuracy on a CNC turning center. It is shown that using the proposed measurement system results in workpiece setting time decrease and workpiece machining accuracy improvement. The development of the on‐machine measurement system makes the fine touch sensor extremely attractive for CNC machine retrofitting.

This paper aims to define imminent and future key aspects in innovative production machines and systems but more specifically to focus on the automation and control aspects.

The foresight analysis is based on the state‐of‐the‐art of current manufacturing technologies with a setup of key enabling features and a roadmap research.

The paper finds that more integration of current and future technology development is required to build a strong platform for various applications featured with interoperability, trust, security and protection. Autonomy and close collaboration aspects in machines remain as crucial targets for the near future. An immediate action is required on smart strategies for the design patterns and agents to enable intuitive components for high quality dynamic user interfaces. This will allow rapid configuration and adaptation to new manufacturing tasks with highly improved machine learning.

The paper describes the future of key aspects required to move the production, automation and control systems forward.

For using wireless sensors to monitor spindle units without opening the spindle shell to replace the battery, harvesting the waste heat from spindle units of machine tools for thermoelectric generation to drive wireless sensors is studied in this paper. The paper aims to discuss these issues.

In this paper, the thermal network method and the analogies between electrical and thermal domains are used in the simulation of power output performance of thermoelectric generation on a rotating spindle. After that, experiments are done to obtain the real power output performance of the generation and evaluate the feasibility to drive wireless sensors.

The paper provides that the output voltage of the thermoelectric generations was nearly linear with the rotating speed of the spindle, the output voltage was sensitive to the fixed position of the generations, and the thermoelectric system could drive the wireless sensor well most of the time during continuous operation of the spindle.

It is found that the thermoelectric generation could not provide enough power in the early start-up stage of the spindle rotation, so a high-efficiency power manage system, which will be studied in the future research, is needed to handle this problem.

The paper includes implications for the development of self-powered wireless sensors in the spindle unit for machine tool monitoring.

The paper develops a model of the power output performance of thermoelectric generation on a rotating spindle and tests the feasibility to drive wireless sensors with this power.

A new cutting tool is always well-defined and sharp at the onset of the metal cutting process and gradually losses these properties as the machining process advances. Similarly, at the beginning of the machining process, amplitude of tool vibrations is considerably low and it increases gradually and peaks at the end of the service period of the cutting tool while machining. It is significant to provide a corresponding real-time varying damping to control this chatter, which directly influences accuracy and quality of productivity. This paper aims to review the literature related to the application of smart fluid to control vibration in metal cutting and also focused on the challenges involved in the implementation of active control system during machining process.

Smart dampers, which are used as semi-active and active dampers in metal cutting, were reviewed and the research studies carried out in the field of the magnetorheological (MR) damper were concentrated. In smart materials, MR fluids possess some disadvantages because of their sedimentation of iron particles, leakage and slow response time. To overcome these drawbacks, new MR materials such as MR foam, MR elastomers, MR gels and MR plastomers have been recommended and suggested. This review intents to throw light into available literature which exclusively deals with controlling chatter in metal cutting with the help of MR damping methods.

Using an MR damper popularly known for its semi-active damping characteristics is very adaptable and flexible in controlling chatter by providing damping to real-time amplitudes of tool vibration. In the past, many researchers have attempted to implement MR damper in metal cutting to control vibration and were successful. Various methods with the help of MR fluid are illustrated.

A new cutting tool is always well-defined and sharp at the onset of metal cutting process and gradually losses these properties as the machining process advances. Similarly, at the beginning of the machining process, amplitude of tool vibrations is considerably low and it increases gradually and peaks at the end of service period of cutting tool while machining. Application of MR damper along with the working methodology in metal cutting is presented, challenges met are analyzed and a scope for development is reviewed.

This study provides corresponding real-time varying damping to control tool vibration which directly influences accuracy and quality of productivity. Using an MR damper popularly known for its semi-active damping characteristics is very adaptable and flexible in controlling chatter by providing damping to real-time amplitudes of tool vibration.

This study attempts to implement smart damper in metal cutting to control vibrations.

It is significant to provide corresponding real-time varying damping to control tool vibration which directly influences accuracy and quality of productivity.

At present, one of the key equipment in pillar industries is a large rotating machinery. Conducting regular health monitoring is important for ensuring safe operation of the large rotating machinery. Because vibrations sensors play an important role in the workings of the rotating machinery, measuring its vibration signal is an important task in health monitoring. This paper aims to present these.

In this work, the contact vibration sensor and the non-contact vibration sensor have been discussed. These sensors consist of two types: the electric vibration sensor and the optical fiber vibration sensor. Their applications in the large rotating machinery for the purpose of health monitoring are summarized, and their advantages and disadvantages are also presented.

Compared with the electric vibration sensor, the optical fiber vibration sensor of large rotating machinery has unique advantages in health monitoring, such as provision of immunity against electromagnetic interference, requirement of less insulation and provision of long-distance signal transmission.

Both contact vibration sensor and non-contact vibration sensor have been discussed. Among them, the electric vibration sensor and the optical fiber vibration sensor are compared. Future research direction of the vibration sensors is presented.

Explains that the rapid growth of artificial intelligence techniques, especially neural networks and knowledge‐based systems, have paved the way for the development of an intelligent and real‐time manufacturing information system. By efficiently utilizing the specific domain representation in a production cell, an intelligent system can manage the complex issues concerning the structure and character of the product, goals of the manufacturing unit and provide production guidance accordingly. Addresses issues in manufacturing intelligence through two case studies that demonstrate the feasibility of a real‐time quality control in changing environmental conditions. The quality and the factor of acceptability are determined by the intelligent agent. These intelligent agents involve the use of an artificial neural network system and, in some cases, a knowledge‐based system to control and operate, in real‐time, the functions of an inspection process in manufacturing. Addresses the design issues of interest, especially setting up global routines which can be used in a common platform to control a machine tool, interpret the sensor inputs, monitor the quality of products, and take corrective actions on a real‐time basis.

The US National Bureau of Standards recently showed its Automated Manufacturing Research Facility. Advanced techniques and communication developed are aimed to help US industry.

The paper aims to present a systematic literature review to analyze interrelated enablers of Industry 4.0 for implementation. Industry 4.0 is an integrated manufacturing strategy embedded with disruptive technologies. Adapting these technologies with the present industrial scenario is dependent on understanding the dynamics of various critical enablers in the existing literature. In this paper, an effort has been taken to validate and reinforce these enablers by experts in the field of Industry 4.0 for implementation.

A mixed-methodology is designed in this paper. A text mining approach with an expert’s linguistic assessment method is planned to discover the enablers from literature 2010 to 2019. The most critical enablers and their dependencies on other enablers are studied by using correlation analysis.

The research explores the power driving enablers in three groups: technology, features and requirements for implementing Industry 4.0 in the existing factory. In each group, a high degree of associated and dependent enablers is fragmented in detail.

This paper will benefit the research communities and practitioners to understand the significance of an integrated ecosystem of Industry 4.0 technologies, features and requirements for implementation.

The text mining approach integrated with expert’s linguistic assessment to explore the pairwise relationship among the enablers using word correlation is a novel approach in this paper. Moreover, to best of the authors’ knowledge, this is the first-ever attempt to conduct a structured literature review combined with text analysis and linguistic assessment to identify the enablers of Industry 4.0 for implementation.

Aims to describe the new tendency of Japanese robotic industry observed at the International Robot Exhibition 2005 in Tokyo.

Reports new robots, robotic systems and research.

Finds that Japanese robotics is trying to support the future direction of the nation.

Introduces an approach to study what is going on in the Japanese robotic community based on the social needs of the country.