Job adjustment strategy for predictive maintenance in semi-fully flexible systems based on machine health status

Complex systems consist of multiple machines that are designed with a certain extent of redundancy to control any unanticipated events. The productivity of complex systems is highly affected by unexpected simultaneous machine failures due to overrunning of machines, improper maintenance, and natural characteristics. We proposed realistic configurations with multiple machines having several flexibilities to handle the above issues. The objectives of the proposed model are to reduce simultaneous machine failures by slowing down the pace of degradation of machines, to improve the average occurrence of the first failure time of machines, and to decrease the loss of production. An approach has been developed using each machine’s degradation information to predict the machine’s residual life based on which the job adjustment strategy where machines with a lower health status will be given a high number of jobs to perform is proposed. This approach is validated by applying it in a fabric weaving industry as a real-world case study under different scenarios and the performance is compared with two other key benchmark strategies.This work has been funded by the Department of Science and Technology, Science and Engineering Research Board (DST-SERB), a statutory body established through an Act of Parliament: SERB Act 2008, Government of India with sanction order no. ECR/2016/001808, and also by the FCT-Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Investigation of degradation and upgradation models for flexible unit systems: a systematic literature review

Research on flexible unit systems (FUS) with the context of descriptive, predictive, and prescriptive analysis have remarkably progressed in recent times, being now reinforced in the current Industry 4.0 era with the increased focus on integration of distributed and digitalized systems. In the existing literature, most of the work focused on the individual contributions of the above mentioned three analyses. Moreover, the current literature is unclear with respect to the integration of degradation and upgradation models for FUS. In this paper, a systematic literature review on degradation, residual life distribution, workload adjustment strategy, upgradation, and predictive maintenance as major performance measures to investigate the performance of the FUS has been considered. In order to identify the key issues and research gaps in the existing literature, the 59 most relevant papers from 2009 to 2020 have been sorted and analyzed. Finally, we identify promising research opportunities that could expand the scope and depth of FUS.The project is funded by the Department of Science and Technology, Science & Engineering Research Board (DST-SERB), Statutory Body Established through an Act of Parliament: SERB Act 2008, Government of India with Sanction Order No ECR/2016/001808, and also by FCT—Fundação para a Ciência e Tecnologia through the R&D Units Project Scope: UIDB/00319/2020

Fault Adaptive Workload Allocation for Complex Manufacturing Systems

This research proposes novel fault adaptive workload allocation (FAWA) strategies for the health management of complex manufacturing systems. The primary goal of these strategies is to minimize maintenance costs and maximize production by strategically controlling when and where failures occur through condition-based workload allocation. For complex systems that are capable of performing tasks a variety of different ways, such as an industrial robot arm that can move between locations using different joint angle configurations and path trajectories, each option, i.e. mission plan, will result in different degradation rates and life-expectancies. Consequently, this can make it difficult to predict when a machine will require maintenance, as it will depend not only on the type and quality of the machine, but the actual tasks and mission plans it is performing. Furthermore, effective maintenance planning becomes increasingly challenging when dealing with complex systems, such as manufacturing production lines, that have multiple machines all performing different tasks, as the different degradation rates of each task will likely cause sporadic failures, leading to excessive work stoppages and lost production. In response, this work proposes novel strategies for optimizing maintenance schedules through fault adaptive workload allocation (FAWA). This work will show how we can alternate between multiple mission plans and task assignments to control degradation across multiple components, guiding failures to occur at optimal times and locations. We will present two unique strategies for degradation control. The first strategy attempts to synchronize maintenance by utilizing multiple mission plans and task assignments, such that the healthiest components do the most work, whenever possible, in order to compensate for the more degraded components. This promotes balanced degradation and synchronized failures across all components, allowing the number of work stoppages to be minimized. The second strategy involves desynchronizing maintenance by alternating between mission plans and task assignments where the healthiest components do either the most work or the least work in order to maintain an optimal difference between component degradation rates, such that overlapping failures are minimized. In this work, FAWA is applied to several case studies involving two types of manufacturing systems: industrial robot arms and 3D printers

Residual life prediction and degradation-based control of multi-component systems

The condition monitoring of multi-component systems utilizes multiple sensors to capture the functional condition of the systems and allows the sensor information to be used to reason about the health information of the systems or components. Chapter 3 considers the situation when sensor signals capture unknown mixtures of component signals and proposes a two-stage vibration-based methodology to identify component degradation signals from mixed sensor signals in order to predict component-level residual lives. Specifically, we are interested in modeling the degradation of systems that consist of two or more identical components operating under similar conditions. Chapter 4 focuses on the interactive relationship between tool wear (component degradation) and product quality degradation (sensor information) that widely exists in multistage manufacturing processes and proposes a high-dimensional stochastic differential equation model to capture the interaction relationship. Then, real-time quality measurements are incorporated to online predict the residual life of the system. Chapter 5 develops a strategy of dynamic workload adjustment for parallel multi-component systems in order to control the degradation processes and failure times of individual components, for the purpose of preventing the overlap of component failures. This chapter opens a new research direction that focuses on the active control of degradation rather than only the modeling part.Ph.D

Study of dynamic workload assignment strategies on production performance

As maintenance has grown to be seen as a prospective tool for production value generation and business performance improvement, it can no longer be considered as isolated from other production activities. Studies have shown that the degradation process of machines is dependent on the operation being performed (e.g., higher workload results in faster degradation). However, the decision-making in maintenance planning with dynamic operation/workload adjustment considerations has not been addressed until recently. Moreover, the existing approaches attempting to tackle this problem have overlooked the fact that dynamics exist in both external production environment and internal production conditions and thus prove to be inefficient to react to unexpected situations arising. This paper has explored the impacts of different workload adjustment strategies on system production performance by a numerical study using agent-based simulation. A detailed discussion is given on the implication of the simulation outcome, based on which some insights into potential future work are also presented.EU H2020 Acknowledgments to financial support of Cambridge Trust and China Scholarship Counci

Collaborative Networks, Decision Systems, Web Applications and Services for Supporting Engineering and Production Management

This book focused on fundamental and applied research on collaborative and intelligent networks and decision systems and services for supporting engineering and production management, along with other kinds of problems and services. The development and application of innovative collaborative approaches and systems are of primer importance currently, in Industry 4.0. Special attention is given to flexible and cyber-physical systems, and advanced design, manufacturing and management, based on artificial intelligence approaches and practices, among others, including social systems and services

An Efficient Analysis on Performance Metrics for optimized Wireless Sensor Network

Wireless Sensor Networks have the revolutionary significance in many new monitoring applications and self-organized systems. Based on the nature of application WSN are needed to support various levels of Quality of Services. Quality of service parameters are most significant aspect in WSN during data transmission from sensor nodes to sink. This paper surveys the factor on reliability, predictability, sustainability, optimal clustering and scheduling by analyzing various models existing in WSN. A network that satisfies all these Qos parameters ensures outstanding throughput in performance. We concluded by exploring some of the dimensions for research interest and addressed open issues ahead to enhance the performance of WSNs

Draft guidelines concerning E&D issues: The TELSCAN handbook of design guidelines for usability of systems by elderly and disabled drivers and travellers. Version 2

Draft guidelines concerning E&D issues: The TELSCAN handbook of design guidelines for usability of systems by elderly and disabled drivers and travellers. Version

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 133)

This special bibliography lists 276 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in September 1974