Offshore wind turbine drive train technology is evolving as developers increase size, aim to maximise availability and adapt changing electricity grid requirements. This work first of all explores offshore market trends observed in Europe, providing a comprehensive overview installed planned capacity, showing clear shift from smaller high-speed geared machines larger direct-drive machines. To e...

Abstract Electric vehicles (EV) represent a key technology to achieve low-carbon transportation objective, whist induction motors are one of the promising topologies. The reliability these machines is crucial minimize downtime, cost and unwanted human lives. Although several techniques utilized in condition monitoring fault detection electrical machines, there still no single technique that pro...

Fault detection at the early stage is very important in modern industrial processes to avoid failure with life-threatening results and reduce cost of maintenance machine downtime. In this paper, we present a workflow for building fault diagnosis system based on acoustic emission (AE) using learning (ML) techniques. Our approach implemented an embedded device internet things (IoT) connectivity r...

Joint optimization models were developed combining group preventive maintenance of a series system and production scheduling. In this paper, we propose a joint optimization model to minimize the total cost including production cost, preventive maintenance cost, minimal repair cost for unexpected failures and tardiness cost. The total cost depends on both the production process and the machine m...

Cloud computing is emerging as an increasingly popular computing paradigm, allowing dynamic scaling of resources available to users as needed. This requires a highly accurate demand prediction and resource allocation methodology that can provision resources in advance, thereby minimizing the virtual machine downtime required for resource provisioning. In this paper, we present a dynamic resourc...

Through a mechatronic system, the project of linear blower was born from difficulty found by textile industry (which uses cotton as raw material) in keeping their machines and equipment proper working conditions without residue accumulation, causing several problems damaging final product. To avoid this problem, solution used until then manual cleaning process, which demanded qualified labor fo...

Abstract Large rotating machines are critical equipment in many process industries, such as energy, chemical, and power generation. Due to high speed tremendous momentum of the rotor, centrifugal force may lead flying apart rotor parts, which brings a great threat operation safety. Early detection prediction potential failures could prevent catastrophic plant downtime economic loss. In this pap...

Background. In current economic downturn, industries have to set good control on production cost, tomaintain their profitmargin.Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model i...

J. Inst. Brew. 116(4), 354–359, 2010 The efficiency of bottling plants typically ranges between 40 to 70%. Automatic conditioning monitoring helps to find critical points in a plant and supports the operator in optimizing the plant. But bottling plants are complex lines of several linked machines and currently critical points can only be identified manually. This paper presents a model-based ef...

In Industry 4.0, machine data acquisition plays an important role in improving overall performance on the factory floor by monitoring processes, providing feedback, and integrating information with other machines. Leveraging these hidden instantaneously to reduce downtime could also minimize efforts determining causes of maintenance issues. This paper explores a novel method bringing into Indus...