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Reconfigurable vibrating screen (RVS) is an innovative beneficiation machine designed at Tshwane University of Technology, Republic of South Africa (RSA); with adjustable screen structure to ensure sorting, sizing and screening of varying mineral particles (sizes and quantities) demanded by the customers in a cost-effective manner through the screen structure geometric transformation. In order to ensure that this machine is optimally maintained and managed when utilized in surface and underground mining industries, there is a need to establish or ascertain the best maintenance practices that would be used in optimally managing the RVS machine using decision making techniques. In view of this, the purpose of this paper is to ascertain the best maintenance practices that would be used to optimally maintain and manage the RVS machine when used in surface and underground mines.

Decision making techniques such as weighted decision matrix (WDM) and analytical hierarchy process (AHP) were used in this research work to establish the best maintenance practice for optimally maintaining and managing the RVS machine using relevant literature survey on maintenance management systems as well as the different maintenance criteria decision indices obtained from different conventional vibrating screen machine manufacturers and maintenance experts.

Based on the results obtained from the WDM analysis, it was anticipated that e-maintenance (e-M) system embedded with diagnosing and prognosing algorithms; with a cumulative weight score of 2.37 is the best maintenance practice for managing the RVS machine when used in surface mines, while AHP with deeper decision making analysis anticipated that the robotic-driven maintenance (RM) system with an important decision criteria; safety, and a cumulative hierarchy score of 28.6 percent, supported by e-M management system with a cumulative hierarchy score of 17.6 percent are the best maintenance mix that could be used in optimally maintaining and managing the RVS machine, when used in a craggy and hazardous underground mining environment.

To this effect, it could be anticipated that e-M management system (endowed with the ability to detect fault on the machine, diagnose and prognose the different subsystems of the RVS machine and ascertain the reconfiguration time and process of the RVS machine in recovering production loss during the maintenance of the machine as well as meeting customers demand, etc.) is the best maintenance practice for optimally maintaining the RVS machine when utilized in surface mines while both e-M management system and RM management system (endowed with the ability to carry out automated maintenance tasks achievement under little or no maintenance manager intervention) are also anticipated as the best customized maintenance practices mix that could be used in optimally maintaining the RVS machine, when used in dangerous and hazardous underground mining environment.

This maintenance management system evaluation and selection for optimal RVS machine functionality will serve as a useful information to different mining machines (and other related machines) maintenance managers, in selecting the best maintenance management system for ensuring optimal functionality, reliability and maintainability of machines used in their industries.

In manufacturing, dedicated machine tools and flexible machine tools are failing to satisfy the ever-changing manufacturing demands of short life cycles and dynamic nature of products. These machines are limited when new product designs are introduced. The solution lies in developing responsive machines that can be adjusted or be changed functionally when these change requirements arise. These machines are reconfigurable machines which are becoming the new focus, as they rapidly respond to product variety and volume changes. A sheet metal working machine known as a reconfigurable guillotine shear and bending press machine (RGS&BPM) has been developed. The purpose of this paper is to present a methodology, function-oriented design approach (FODA), which was developed for the design of the RGS&BPM.

The design of the machine is based on the six principles of reconfigurable manufacturing systems (RMSs), namely, modularity, scalability integrability, convertibility, diagnosability and customisability. The methodology seeks to optimise the design process of the RGS&BPM through a design of modules that make up the machine, enable its conversion and reconfiguration. The FODA is focussed on function identification to select the operational function required. Two main functions are recognised for the machine, these being cutting and bending; hence, the design revolves around these two and reconfigurability.

The developed design methodology was tested in the design of a prototype for the reconfigurable guillotine shear and bending press machine. The prototype is currently being manufactured and will be subjected to functional tests once completed. This paper is being presented not only to present the methodology by to show and highlight its practical applicability, as the prototype manufacturers have been enthusiastic about this new approach.

The research was limited to the design methodology for the RGS&BPM, the machine which has been designed to completion using this methodology, with prototype being manufactured.

This study presents critical steps and considerations in the development of reconfigurable machines. The main thrust being to explore the best possibility of developing the machines with dual functionality that will assist in availing the technology to manufacturer. As the machine has been development, the success of the design can be directly attributed to the FODA methodology, among other contributing factors. It also highlights the significance of the principles of RMS in reconfigurable machine design.

The RGS&BM machine is an answer for the small-to-medium enterprises (SMEs), as the machine replaces two machines with one, and the methodology ensures its affordable design. It contributes immensely to the machine availability by eliminating trial and error approaches.

This study presents a new approach to the design of reconfigurable dual machines using principles of RMS. As the targeted market is the SME, it is not limited to that as any entrepreneur may use the machine to their advantage. The design methodology presented contributes to the body of knowledge in dual reconfigurable machine tool design.

Reconfigurable machines tools (RMTs) are gaining momentum as the new solutions to customised products in the manufacturing world. The driving force, among others, behind these machines is the part envelope and the part family of products that they can produce. The purpose of this paper is to propose a new class of RMT known as a reconfigurable guillotine shear and bending press machine (RGS&BPM). A part family of products that this machine can produce is developed using hierarchical clustering methodologies. The development of these part families is guided by the relationship of the parts in the family in terms of complexity and geometry.

Part families cannot be developed in isolation, but that process has to incorporate the machine modules used in the reconfiguration process for producing the parts. Literature was reviewed, and group technology principles explored, to develop a concept that can be used to develop the part families. Matrices were manipulated to generate part families, and this resulted in the development of a dendrogram of six possible part families. A software with a graphic user interface for manipulation was also developed to help generate part families and machine modules. The developed concept will assist in the development of a machine by first developing the part family of products and machine modules required in the variable production process.

The developed concepts assist in the development of a machine by first developing the part family of products and machine modules required in the variable production process. The development of part families for the RGS&BPM is key to developing the machine work envelope and modules to carry out the work. This work has been presented to demonstrate the importance of machine development in conjunction with a part family of products that the machine will produce. The paper develops an approach to manufacturing where part families of products are developed prior to developing the machine. The families of products are then used to develop modules that enable the manufacture of the parts and subsequently the size of the machine.

The research was limited to the development of part families for a new RGS&BPM, which is still under development.

The study reflects the development of reconfigurable machines as a solution to manufacturing challenges in terms of group technology approaches adopted in the design phase. It also highlights the significance of the concepts in the reconfigurable machine tool design. The part families define the machine work envelop and its reconfiguration capability.

The success of the research will usher an alternative to smaller players in sheet metal work. It will contribute to the easy development of the machine that will bridge the high cost of machine tools.

The study contributes to the new approach in sheet metal manufacturing where dedicated machines may be substituted by a highly flexible reconfigurable machine that has a dual operation, making the investment for small to medium enterprises affordable. It also contributes to the body of knowledge in reconfigurable machine development and the framework for such activities, especially in developing countries.

Selection of a suitable location for a quarantine infrastructure represents a complex decision problem, which requires a systematic appraisal of myriads of factors. Quarantine facility in this study is a facility that intends to harbour and treat individuals diagnosed with COVID-19 to prevent the widespread of the virus. COVID-19 is a very contagious pandemic disease, hence, the establishment of critical factors that will embrace the selection of a suitable quarantine facility is of high importance. This paper aims to ascertain the vital few factors that must be considered by decision makers in selecting a suitable quarantine facility.

The aim of this study was achieved through the numerical assessment of identified quarantine location selection factors using the analytical hierarchy process (AHP) and Pareto techniques. The factors, which influences the selection of a suitable quarantine facility for COVID-19 patients were first identified from the literature followed by the pairwise comparison of the factors and random consistency analyses, as well as the ranking of the alternatives based on facility location experts’ opinions.

The study revealed that security, skills availability, cost, readiness, proximity to necessary medical facilities and distance to border, with percentage weight scores of 18%, 16.7%, 15.6%, 10.3%, 9.8% and 6.6% were the critical factors that must be considered during the selection of a quarantine facility for COVID-19 patients.

The results of this paper will help the government and decision makers in locating the quarantine sites for people who tested positive for the COVID-19 virus.

The present study focuses on the application of the decision technique to ascertain critical factors that embrace suitable quarantine facility selection. Combination of AHP and Pareto techniques for prioritization of conflicting factors to be considered in selecting the most suitable location for a quarantine facility has not been reported by existing literature.

The purpose of this paper is twofold: an approach is proposed to determine the optimum replacement time for shovel teeth; and a risk-quantification approached is developed to derive a confidence interval for replacement time.

The risk-quantification approach is based on a combination of Monte Carlo simulation and Markov chain. Monte Carlo simulation whereby the wear of shovel teeth is probabilistically monitored over time is used.

Results show that a proper replacement strategy has potential to increase operation efficiency and the uncertainties associated with this strategy can be managed.

The failure time distribution of a tooth is assumed to remain “identically distributed and independent.” Planned tooth replacements are always done when the shovel is not in operation (e.g. between a shift change).

The proposed approach can be effectively used to determine a replacement strategy, along with the level of confidence level, for preventive maintenance planning.

The originality of the paper rests on developing a novel approach to monitor wear on mining shovels probabilistically. Uncertainty associated with production targets is quantified.

The ATF 10/20 from Electrovert (UK) is a bench‐top wave soldering system, whose competent ‘no frills’ ease of maintenance design combined with sound build quality makes it an ideal entry level machine.

The purpose of this review paper is to address the substantial challenges of the outdated exoskeletons used for rehabilitation and further study the current advancements in this field. The shortcomings and technological developments in sensing the input signals to enable the desired motions, actuation, control and training methods are explained for further improvements in exoskeleton research.

Search platforms such as Web of Science, IEEE, Scopus and PubMed were used to collect the literature. The total number of recent articles referred to in this review paper with relevant keywords is filtered to 143.

Exoskeletons are getting smarter often with the integration of various modern tools to enhance the effectiveness of rehabilitation. The recent applications of bio signal sensing for rehabilitation to perform user-desired actions promote the development of independent exoskeleton systems. The modern concepts of artificial intelligence and machine learning enable the implementation of brain–computer interfacing (BCI) and hybrid BCIs in exoskeletons. Likewise, novel actuation techniques are necessary to overcome the significant challenges seen in conventional exoskeletons, such as the high-power requirements, poor back drivability, bulkiness and low energy efficiency. Implementation of suitable controller algorithms facilitates the instantaneous correction of actuation signals for all joints to obtain the desired motion. Furthermore, applying the traditional rehabilitation training methods is monotonous and exhausting for the user and the trainer. The incorporation of games, virtual reality (VR) and augmented reality (AR) technologies in exoskeletons has made rehabilitation training far more effective in recent times. The combination of electroencephalogram and electromyography-based hybrid BCI is desirable for signal sensing and controlling the exoskeletons based on user intentions. The challenges faced with actuation can be resolved by developing advanced power sources with minimal size and weight, easy portability, lower cost and good energy storage capacity. Implementation of novel smart materials enables a colossal scope for actuation in future exoskeleton developments. Improved versions of sliding mode control reported in the literature are suitable for robust control of nonlinear exoskeleton models. Optimizing the controller parameters with the help of evolutionary algorithms is also an effective method for exoskeleton control. The experiments using VR/AR and games for rehabilitation training yielded promising results as the performance of patients improved substantially.

Robotic exoskeleton-based rehabilitation will help to reduce the fatigue of physiotherapists. Repeated and intention-based exercise will improve the recovery of the affected part at a faster pace. Improved rehabilitation training methods like VR/AR-based technologies help in motivating the subject.

The paper describes the recent methods for signal sensing, actuation, control and rehabilitation training approaches used in developing exoskeletons. All these areas are key elements in an exoskeleton where the review papers are published very limitedly. Therefore, this paper will stand as a guide for the researchers working in this domain.