Online Tool Condition Monitoring Based on Parsimonious Ensemble+

Accurate diagnosis of tool wear in metal turning process remains an open challenge for both scientists and industrial practitioners because of inhomogeneities in workpiece material, nonstationary machining settings to suit production requirements, and nonlinear relations between measured variables and tool wear. Common methodologies for tool condition monitoring still rely on batch approaches which cannot cope with a fast sampling rate of metal cutting process. Furthermore they require a retraining process to be completed from scratch when dealing with a new set of machining parameters. This paper presents an online tool condition monitoring approach based on Parsimonious Ensemble+, pENsemble+. The unique feature of pENsemble+ lies in its highly flexible principle where both ensemble structure and base-classifier structure can automatically grow and shrink on the fly based on the characteristics of data streams. Moreover, the online feature selection scenario is integrated to actively sample relevant input attributes. The paper presents advancement of a newly developed ensemble learning algorithm, pENsemble+, where online active learning scenario is incorporated to reduce operator labelling effort. The ensemble merging scenario is proposed which allows reduction of ensemble complexity while retaining its diversity. Experimental studies utilising real-world manufacturing data streams and comparisons with well known algorithms were carried out. Furthermore, the efficacy of pENsemble was examined using benchmark concept drift data streams. It has been found that pENsemble+ incurs low structural complexity and results in a significant reduction of operator labelling effort.Comment: this paper has been published by IEEE Transactions on Cybernetic

Towards Interference Aware IoT Framework: Energy and Geo-location based Modelling

In multi-hop wireless communication, a sensor node must consume its energy efficiently for relaying data packets. However, most of the IoT-devices are equipped with limited battery power and computing resources for wireless communication thus energy optimization becomes one of the major concerns in wireless sensors routing design. The wireless technologies usually use unlicensed frequency bands of 2.4 GHz to transmit the data. Due to the broadcasting medium, the wireless transmission interferes with the reception of surrounding radios. As a result, data transmission failure increases and thus low communication quality. Therefore, one of the best solutions of this problem is to select the hop distance node that has a few neighbour nodes to disseminate a packet until it reaches the ultimate receiver. The new routing selects the node that has few neighbouring nodes and thus less interference. In another word, the scheme finds a better load balancing and thus minimizes the probability of overload on a sensor node. It also introduces a new clustering algorithm around a single base station that could shorten the transmission distances. This approach periodically selects the cluster heads (CHs) according to its location from the final destination. Extensive simulation studies reveal that the proposed algorithm finds the best routing technique and clustering formation to forward the traffic and thereby minimizes the interference ratio. In addition, the proposed protocol achieves low energy consumption and longer network lifetime than other popular protocols

Stepping out of planned obsolescence into the circular economy: the emergence, effects, and ethics in the smartphone industry

A constructive debate on the circular economy entails rethinking planned obsolescence. The increased production and use of consumer electronics, together with their high replacement rate substantially increases electronic waste. Planned obsolescence consist of multiple strategies for rendering a product obsolete. In recent years, we have observed a shift from aesthetic obsolescence to technological obsolescence in for example, smartphones. As regards hardware, the life span of a product is artificially reduced by designing components that cannot be disassembled without damaging the product. Software obsolescence, on the other hand, comprises updates that slow down devices, or create incompatibility between operating systems and running applications. This paper investigates these practices in the smartphone industry. Based on the analysis of the literature we compare planned obsolescence strategies adopted by major companies against circular economy strategies and policies recently implemented. We assess the embodiment of the strategies by analysing product features and indexes of repairability in smartphones and characterise technological obsolescence considering hardware, firmware and software. Our conclusions suggest that tackling planned obsolescence requires policymaking that establishes guidelines for reliability to strengthen indexes of repairability as information to consumer