Predictive Maintenance

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	Predictive Maintenance

Predictive Maintenance

Formal	Predictive maintenance is a technique to predict the future failure point of a machine component, so that the component can be replaced, based on a plan, just before it fails. Thus, equipment downtime is minimized, and the component lifetime is maximized. Read More
Practical	On the basis of real-time data, all relevant parameters of the machines involved in the manufacturing process are acquired and evaluated for anomalies by means of stream analytics. In a subsequent machine learning process, specific fault patterns and the causes of a problem are detected in good time. This results in fewer rejects and maximum availability over the entire life cycle of the production line. The requirements on machine operating times vary depending on the specific branch of industry and its product cycles. While this could be up to 30 years in the aerospace sector, it is a matter of just a few months in the case of fast-moving goods, such as smartphones. With the aim of enabling an accurate assessment of the future performance of the machine or one of its components, intelligent predictive maintenance systems interconnect the largest possible amount of data from decentralized sources for the purpose of analysis. Read More
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Formal

Predictive maintenance is a technique to predict the future failure point of a machine component, so that the component can be replaced, based on a plan, just before it fails. Thus, equipment downtime is minimized, and the component lifetime is maximized.

Practical

On the basis of real-time data, all relevant parameters of the machines involved in the manufacturing process are acquired and evaluated for anomalies by means of stream analytics. In a subsequent machine learning process, specific fault patterns and the causes of a problem are detected in good time. This results in fewer rejects and maximum availability over the entire life cycle of the production line. The requirements on machine operating times vary depending on the specific branch of industry and its product cycles. While this could be up to 30 years in the aerospace sector, it is a matter of just a few months in the case of fast-moving goods, such as smartphones. With the aim of enabling an accurate assessment of the future performance of the machine or one of its components, intelligent predictive maintenance systems interconnect the largest possible amount of data from decentralized sources for the purpose of analysis.

	Bright Wolf Bright Wolf is a technology provider and trusted partner for Fortune 1000 companies building transformative Enterprise-class connected product solutions. We offer complete design consulting, development, and systems integration services for Industrial IoT projects, as well as production operational support to commercialize and maintain successful connected offerings at scale. Our industrial reference applications and solution templates bring a faster path to production on the Public Cloud, in your datacenter, and at the edge, providing complete data modeling and management, sophisticated policy-driven access controls, device lifecycle management, and out-of-the-box enterprise system integration. Our customized solutions leverage your choice of cloud infrastructure and tools, to which we bring decades of expertise with industrial controls and protocols, embedded systems, and intelligence at the edge. Global production deployments include Manufacturing, Oil & Gas, Healthcare, Agriculture, Smart Building, Heavy Equipment, and other industries for Asset Management, Predictive Maintenance, and Yield Optimization. Bright Wolf solutions have been deployed on Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform.
	FogHorn FogHorn is a leading developer of “edge intelligence” software for industrial and commercial IoT applications. FogHorn’s software platform brings the power of Machine Learning and advanced analytics to the On-Premise edge environment enabling a new class of applications for advanced monitoring and diagnostics, asset performance optimization, operational intelligence and Predictive Maintenance use cases.
	Ascalia Ascalia is a UK and Croatia based company that provides software and hardware solutions aimed at reducing resource and energy consumption in cities and industry.We developed our hardware and software in a way that it can be easily customizable to conform with our client's goals. Our goal is to accelerate IoT development and empower our clients to easily install and benefit from the IoT based solutions.Ascalia provides a cost-effective package of integrated software and hardware that guarantees our clients a secure and timely achievement of their business objectives as well as significant cost savings.
	Hitachi Vantara (Hitachi) Hitachi Vantara, a wholly owned subsidiary of Hitachi, Ltd., helps data-driven leaders find and use the value in their data to innovate intelligently and reach outcomes that matter for business and society. They combine technology, intellectual property and industry knowledge to deliver data-managing solutions that help enterprises improve their customers' experiences, develop new revenue streams, and lower business costs. Only Hitachi Vantara elevates your innovation advantage by combining deep information technology (IT), operational technology (OT) and domain expertise. They work with organizations everywhere to drive data to meaningful outcomes.
	Infoteam Software (Suzhou) Full integrator and consulting for Industry 4.0 solutions. Specialized in Digital Transformation, Industry 4.0, Data Analytics, VR/AR.Project Workshops, Planning, Industry 4.0 strategy, Industry 4.0 new business models.For more information pls. get in touch with us: consulting@infoteamcn.com

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Predictive Maintenance

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