Accelerating the Industrial Internet of Things
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Number of Case Studies65
Stepping up Production While Keeping Costs Down with Smarter Maintenance
Stepping up Production While Keeping Costs Down with Smarter Maintenance
To achieve its goal of doubling production capacity while keeping tight control of costs, major shoe manufacturer PT Chang Shin Indonesia set out to unlock greater efficiencies in its operations.
Large Oil Producer Leverages Advanced Analytics Platform
Large Oil Producer Leverages Advanced Analytics Platform
Approximately 17,000 wells in the customer's portfolio have beam pump artificial lift technology. While beam pump technology is relatively inexpensive compared to other artificial lift technology, beam pumps fail frequently, at rates ranging from 66% to 95% per year. Unexpected failures result in weeks of lost production, emergency maintenance expenses, and costly equipment replacements.
Big Data and Predictive Maintenance
Big Data and Predictive Maintenance
Predictive maintenance refers to techniques that help determine the condition of in-service equipment in order to predict and/or optimize when maintenance should be performed. Predictive maintenance is one of the most important benefits of the Industry 4.0 revolution. 
Number of Hardware186
ADC Converter
ADC Converter
Dual Channel Dual ADC Delta-Sigma 110ksps 24-bit Serial 16-Pin SSOP Bulk
Display Driver
Display Driver
VFD DRVR 5.5V 25mA 44-Pin PQFP Tray
LED Driver
LED Driver
LED DRVR 9V/12V/15V/18V/24V 9-Pin
Number of Software70
Teamcenter
Teamcenter
Teamcenter provides cross-domain design data management through integrations with the MCAD, ECAD, software development, and simulation tools and processes your design teams use every day. You can manage, find, share and re-use multi-domain data across geographically distributed design centers through a single, secure source of product design and simulation data. You can understand the complex relationships and dependencies between requirements and all the subsystems and design domains across all the possible configurations of the product, even as changes are introduced. You can also create assemblies from parts generated by multiple suppliers that involve complex interactions of subsystems, then prepare and validate the readiness of the design and bill of materials for fabrication, assembly and test.By integrating your current multi-domain design tools with Teamcenter, you can transform otherwise disconnected tools and processes into a single, cross-domain design data management environment that enables you to lower costs, improve quality, and increase design productivity.
Apama
Apama
Imagine how responsive your enterprise could be if you could glean real-time insights from all that big fast data—data streaming in from global markets, mobile devices, the Internet of Things (IoT), internal transactional systems and a myriad of other sources. You can be that event-driven enterprise by using Apama. Software AG's Apama Streaming Analytics—supporting predictive analytics—is the world’s #1 platform for streaming analytics and intelligent automated action on fast-moving big data. With Apama, you can analyze and act on high-volume business operations in real time.
Avantis Condition Manager
Avantis Condition Manager
A Condition Management solution that collects and analyzes real-time diagnostics from all plant production assets and drives appropriate action to improve overall asset performance and manage the appropriate operations, engineering and maintenance actions. Avantis’ Condition Based Maintenance drives predictive conditional alerts real-time, delivers simplicity from complexity and provides predictive maintenance management with the resultant improvement in asset integrity.
Number of Suppliers39
Humaware
Humaware have developed a suite of innovative data driven tools that provides users with a preventative maintenance capability that detects and diagnoses defects to predict and prevent asset failure. Implementation of our data driven toolset enables organisations to develop effective asset management strategies to enhance condition monitoring systems and realise the benefits of investments in predictive maintenance.
DataRPM
DataRPM is an award-winning predictive analytics company focused on delivering the next generation predictive maintenance solutions for the Industrial IoT. DataRPM platform automates data science leveraging the next frontier in machine learning known as meta-learning, which is machine learning on machine learning. The platform increases prediction quality and accuracy by over 300% in 1/30th the time and resources delivering 30% in cost savings or revenue growth for business problems around predicting asset failures, reducing maintenance costs, optimizing inventory and resources, predicting quality issues, forecasting warranty and insurance claims and managing risks better.DataRPM's advisory board consists of industry luminaries from companies such as Google, Hortonworks, Oracle, Cloudera, EMC, Facebook and Booz Allen Hamilton. Headquartered in Redwood City, California, the company is privately held. Customers of DataRPM include companies like GE, Cisco, Jaguar, Orange and similar Fortune 500 companies.
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.
Number of Use Cases17
Condition-based Maintenance (CBM)
Condition-based Maintenance (CBM)
Condition-based Maintenance (CBM) or predictive maintenance is the science of maintaining physical assets over time, in order to maximize their return on those assets. It is enabled by sensors and data analytics that provide visibility into the current and future status of assets.
Equipment Efficiency Optimization
Equipment Efficiency Optimization
Optimizing the efficiency of equipment has a significant impact on profits and shareholder value. It affects productivity an quality.
Asset Efficiency
Asset Efficiency
Asset Efficiency refers to the process of analyzing the health of an asset. The health of an asset in itself relates to the asset's utility, its need to be replaced, and its need for maintenance. It can be broken down into three key components:1. Monitoring: Tracking the actual health and viability of the asset2. Diagnostic Analysis: Comparing new, real-time data to relevant data from the past in order to detect any anomalies.3. Prognostics: Given past data, algorithms are developed to determine the remaining useful life of an asset
Number of Terms1
Industrie 4.0
Industrie 4.0
Industry 4.0, Industrie 4.0 or the fourth industrial revolution, is the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things and cloud computing. The term "Industrie 4.0" originates from a project in the high-tech strategy of the German government, which promotes the computerization of manufacturing.Invoking a fourth Industrial Revolution, Industrie 4.0 creates intelligent manufacturing networks where decentralized smart factories can communicate and react to each other autonomously.Industry 4.0 creates what has been called a "smart factory". Within the modular structured smart factories, cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Over the Internet of Things, cyber-physical systems communicate and cooperate with each other and with humans in real time, and via the Internet of Services, both internal and cross-organizational services are offered and used by participants of the value chain.
65 Case Studies
186 Hardware
70 Software
39 Suppliers
17 Use Cases
1 Term
10 Guides
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