Accelerating the Industrial Internet of Things
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Number of Case Studies71
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 Hardware234
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 Software227
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.
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.
OpenDNS Umbrella
OpenDNS Umbrella
OpenDNS Umbrella is a cloud-delivered network security service that protects any device, no matter where it’s located.
Number of Suppliers46
Humaware
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
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.
PREDICT
PREDICT
Predict is a specialized company in real/delayed-time Condition Monitoring, Predictive Diagnostic support, Prognostic and Heath Management.
Number of Use Cases12
Predictive Maintenance (PdM)
Predictive Maintenance (PdM)
The aim of predictive maintenance (PdM) is first to predict when equipment failure might occur, and secondly, to prevent the occurrence of the failure by performing maintenance. Monitoring for future failure allows maintenance to be planned before the failure occurs. Ideally, predictive maintenance allows the maintenance frequency to be as low as possible to prevent unplanned reactive maintenance, without incurring costs associated with doing too much preventive maintenance.Predictive maintenance uses condition-monitoring equipment to evaluate an asset’s performance in real-time. A key element in this process is the Internet of Things (IoT). IoT allows for different assets and systems to connect, work together, and share, analyze and action data.  
Asset Health Management (AHM)
Asset Health Management (AHM)
Asset Health Management refers to the process of analyzing the health of an asset as determined by operational requirements. 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:Monitoring: Tracking the current operating status of the asset.Diagnostic Analysis: Comparing real-time data to historical data in order to detect anomalies.Prognostic Analysis: Identifying and prioritizing specific actions to maximize the remaining useful life of the asset based on analysis of real-time and historical data.
Industrial Digital Thread
Industrial Digital Thread
The digital thread refers to the communication framework that allows a connected data flow and integrated view of the asset’s data throughout its lifecycle across traditionally siloed functional perspectives. The digital thread concept raises the bar for delivering “the right information to the right place at the right time.”The Industrial Digital Thread (IDT) testbed drives efficiency, speed, and flexibility through digitization and automation of manufacturing processes and procedures. It collects information in the design, manufacturing, service and supply-chain setup, and provides access to intelligent analytics for industrial manufacturing and performance data.The Digital Thread integrates design, engineering, manufacturing, and MRO (maintenance, repair, and overhaul) systems, establishing a seamless flow of information. This type of integration employs data and analytics across the complete product life cycle, optimizing efficiency, from design to manufacturing, operations, and maintenance to service in a closed loop. 
Number of Terms2
Predictive Maintenance
Predictive Maintenance
Dependable production planning and maximum machine availability through the avoidance of unscheduled downtime are the practical advantages of what is internationally known as predictive maintenance. 
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.
71 Case Studies
234 Hardware
227 Software
46 Suppliers
12 Use Cases
2 Terms
10 Guides
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