Number of Case Studies113
LumenData Delivers Real-time Predictive Analytics through IoT
LumenData Delivers Real-time Predictive Analytics through IoT
In 2013, LumenData found itself in need of adding new real-time predictive analytics capabilities to its suite of services. To meet this need, LumenData acquired a state-of-the-art streaming data, capture and real-time predictive analytics company. This solved the pure predictive analytics end, but left LumenData with a need to be able to build IoT-targeted services.From an IoT perspective, LumenData was still missing the means to create suitable applications and dashboards that would make it easy for its customers to effortlessly make sense of whatever predictive analysis they might require.
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. 
IIC Condition Monitoring & Predictive Maintenance Testbed
IIC Condition Monitoring & Predictive Maintenance Testbed
The current state of condition monitoring requires manual measurements that are compounded with aging equipment and the retirement of knowledgeable personnel.
Number of Software390
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.Apama Streaming Analytics is built on an in-memory architecture that enables real-time processing of extremely fast, large data volumes—orders of magnitude larger than traditional database-based IT architectures. Data science teams build predictive models in whatever data mining tools they prefer to use, then use Predictive Analytics for Apama to load the models in the PMML format. This step takes a fraction of the time that model deployment ordinarily requires, and eliminates the need for manual coding, cross-checking and error correction. Apama allows for ingesting these models rapidly, making them instantly organic to the business process that they support, as defined by various Apama applications.Apama then probes incoming event data from any device, social media stream or business system with extremely low latency against the imported predictive models for real-time scoring. Predictive Analytics for Apama analyzes this streaming data, which can also be enriched with historic and contextual data-at-rest where necessary, to identify business patterns that have happened or are likely to happen. The platform’s visualizations and visual analytics for business users support both human-oriented and automated intelligent actions, alerts and notifications.
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.Multi-CAD Design Data Management for MCADTeamcenter provides design data management with multi-CAD support so that your design teams can create, manage, visualize, validate and re-use native design data across a wide selection of MCAD systems, including NX and Solid Edge from Siemens PLM Software, as well as AutoCAD®, CATIA®, Inventor®, Pro/ENGINEER® and SolidWorks®. Using our JT 3D visualization standard, you can create integrated multi-CAD designs using parts and components from different MCAD tools. You can collaborate on designs, even if you don’t have access to the MCAD tools that authored them.ECAD Design Data ManagementTeamcenter supports integrations with all major ECAD systems. The rich design data management capabilities for printed circuit board (PCB) and wire harness release management enable you to find the right data quickly. The enterprise-wide ECAD parts library management reduces costs by eliminating inconsistent and inaccurate ECAD part data. The ECAD viewer, ECAD-MCAD exchange support and assembly/test analysis tools promote close collaboration within and across domains and organizational functions.Software Design ManagementTeamcenter provides software design data management by integrating software engineering data and processes with product lifecycle management (PLM). Leveraging a multi-domain lifecycle integration framework, Teamcenter enables the seamless integration of application lifecycle management (ALM) tools, data and processes. With this ALM-PLM integration, you can manage your software designs in a holistic product view, and manage software design processes as an integral part of the overall product lifecycle.Simulation Data and Process ManagementTeamcenter can help you validate performance targets by simulating products across a variety of multi-domain and multi-physics issues. Using Teamcenter capabilities specifically designed for managing models, simulation data, and simulation processes, you can quickly derive and generate the computer-aided engineering (CAE) structure from the MCAD or ECAD structures. For complex products, you may use tens or hundreds of different simulation tools to verify performance targets and meet validation contracts. Teamcenter provides a framework for codeless integration with these tools so that data from Teamcenter can be delivered to the tools. Results can then be captured and stored in Teamcenter along with all the correct associations to design and requirements data.Get Up and Running Quickly with Preconfigured PDMIf you need PDM for your small- or medium-sized business, and your primary focus is to take control of multi-CAD and ECAD data and processes, consider the Teamcenter Rapid Start deployment option. With preconfigured groups, roles and processes based on PDM best practices, you can get up and running with Teamcenter quickly and cost-effectively.
SpiraTeam
SpiraTeam
SpiraTeam is an integrated Application Lifecycle Management (ALM) system that manages your project's requirements, releases, test cases, issues and tasks in one unified environment. With integrated customizable dashboards of key project information, SpiraTeam allows you to take control of your entire project lifecycle and synchronize the hitherto separate worlds of development and testing.dministrator Level ControlDefect TrackingIteration PlanningProject ManagementRelease ManagementRequirements ReviewTask ManagementTest Case TrackingUser Level ManagementVersion Control
Number of Suppliers138
Petasense
Petasense
Petasense is an Industrial Internet of Things startup based in Silicon Valley. They make learning wireless sensors that connect to the cloud to democratize Predictive Maintenance for industrial customers. The vision of the company is to connect, collect and predict for the industrial world to improve operational efficiency and reduce costs.
Humaware (EKE-Electronics)
Humaware (EKE-Electronics)
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.
HAL24K
HAL24K
Number of Organizations1
Zetta Venture Partners
Zetta Venture Partners
Zetta Venture Partners is the first focused fund committed to delivering exceptional returns from the high-growth analytics market. The firm, founded by industry veteran Mark Gorenberg, launched in 2013. With offices in San Francisco and Utah, and a worldwide network of partners, entrepreneurs and investors, Zetta Venture Partners is at the forefront of the next huge and long-lasting investment opportunity. Focused funds deliver exceptional returns. In fact, over the past 10 years, focused funds have outperformed all funds by 72 basis points, according to the National Venture Capital Association. As an analytics-only fund, Zetta delivers the expertise, network and portfolio to create ongoing, exceptional deal flow.
Number of Use Cases19
Predictive Waste Reduction
Predictive Waste Reduction
Predictive waste reduction identifies causes for production waste and prescribes focused actions that minimize rework and scrap. Predictive analytics and automated root cause analysis are employed to anticipate process failures that yield wastage. It includes four steps: monitoring current production performance, predicting excessive waste levels, analyzing the cause of waste issues, and preventing causes for waste and rework.
Predictive Replenishment
Predictive Replenishment
Predictive replenishment anticipates when customers will need to replenish inventory by analyzing sales forecasts and inventory levels. Typically, merchandise is sold to stores on a calendar basis or as a reaction to a purchase order, not based on actual consumption. Stores risk running out of inventory when actual consumption patterns vary from the set schedule, or they must hold excess inventory which ties up working capital. Predictive replenishment considers multiple factors such as seasonality, inventory, ordering patterns, lead time forecasts, special orders, product lifecycle phase, and service level goals, to improve replenishment forecasts for the next period. Most predictive replenishment systems are collaborative, linked with customer's demand forecasting or point of sale systems to automatically gather input into the replenishment forecasting models. Predictive replenishment can also be applied to industrial situations, such as component or raw material inventory in a factory, or spare parts inventory at a utility.
Predictive Quality Analytics
Predictive Quality Analytics
Predictive quality analytics uses statistical algorithms and machine learnings to anticipate quality and safety risks before they occur, offering the opportunity to take timely and targeted countermeasures. As a first step, all available external and internal data sources are prioritized, consolidated, and correlated. Comprehensive data analyses are then performed and predictive models are developed in an iterative process, making use of a variety of evaluation techniques. Depending on the parameters which flow into the model, it is possible with these methods to forecast not only defects that appear shortly in the future but also ones which could lead to a warranty claim in the long term. The models are thus capable of integrating data sources, making efficient data mining possible and leading to user-friendly evaluations which in turn can be converted into easily readable reports for the end-user or managers at the reporting level. Wisely used, predictive quality analytics can lead to significant savings in warranty costs, improve customer satisfaction, and reduce scrap rates.
113 Case Studies
390 Software
138 Suppliers
2 Events
1 Organization
19 Use Cases
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