Predictive Maintenance for Government



Similar documents
Making critical connections: predictive analytics in government

Working with telecommunications

Improving claims management outcomes with predictive analytics

Three proven methods to achieve a higher ROI from data mining

The top 10 secrets to using data mining to succeed at CRM

Recognize the many faces of fraud

Increasing marketing campaign profitability with Predictive Analytics

Easily Identify Your Best Customers

Using Data Mining to Detect Insurance Fraud

IBM SPSS Direct Marketing

Get to Know the IBM SPSS Product Portfolio

Tapping the benefits of business analytics and optimization

Achieving customer loyalty with customer analytics

IBM Predictive Analytics Solutions for Education

Five predictive imperatives for maximizing customer value

IBM Business Analytics: Finance and Integrated Risk Management (FIRM) solution

White Paper March Government performance management Set goals, drive accountability and improve outcomes

Analyzing survey text: a brief overview

IBM Analytical Decision Management

IBM SPSS Modeler Professional

Predictive analytics with System z

Business analytics for manufacturing

IBM Cognos Enterprise: Powerful and scalable business intelligence and performance management

Solve your toughest challenges with data mining

Driving business intelligence to new destinations

Planning successful data mining projects

Empowering intelligent utility networks with visibility and control

How To Use Social Media To Improve Your Business

Delivering a Smarter Shopping Experience with Predictive Analytics:

Bunzl Distribution. Solving problems for sales and purchasing teams by revealing new insights with analytics. Overview

The IBM Cognos family

Setting smar ter sales per formance management goals

Optimizing government and insurance claims management with IBM Case Manager

IBM Cognos Business Intelligence on Cloud

IBM SPSS Text Analytics for Surveys

An integrated approach to managing today s energy and utility assets

Jabil builds momentum for business analytics

Delivering new insights and value to consumer products companies through big data

IBM Software Enabling business agility through real-time process visibility

Solve your toughest challenges with data mining

eircom gains deep insights into customer experience

A proven 5-step framework for managing supplier performance

Predictive Maintenance

Predictive Analytics. Going from reactive to proactive. Mats Stellwall - Nordic Predictive Analytics Enterprise Architect

Predictive Analytics for Donor Management

Insurance customer retention and growth

IBM Tivoli Netcool network management solutions for enterprise

IBM Cognos Analysis for Microsoft Excel

Three Ways to Improve Claims Management with Business Analytics

Overcoming challenges of asset management amid declining federal budgets

White Paper May Seven reports every supply chain executive needs Supply Chain Performance Management with IBM

A full spectrum of analytics you can get yourself

Name: Srinivasan Govindaraj Title: Big Data Predictive Analytics

Go with the flow: Transportation information management solutions from IBM.

Driving Smarter, More Efficient Supply Chains Through Analytics

Harnessing the power of advanced analytics with IBM Netezza

Breaking down silos of protection: An integrated approach to managing application security

Better planning and forecasting with IBM Predictive Analytics

Beyond listening Driving better decisions with business intelligence from social sources

Selecting the right cybercrime-prevention solution

Automating incentive compensation for increased productivity and cost reduction

Addressing government challenges with big data analytics

Strengthen security with intelligent identity and access management

IBM Cognos Insight. Independently explore, visualize, model and share insights without IT assistance. Highlights. IBM Software Business Analytics

Defining a blueprint for a smarter data center for flexibility and cost-effectiveness

Fiserv. Saving USD8 million in five years and helping banks improve business outcomes using IBM technology. Overview. IBM Software Smarter Computing

White Paper February IBM Cognos Supply Chain Analytics

IBM SmartCloud Monitoring

Ten questions to ask when evaluating contract management solutions

IBM InfoSphere Guardium Data Activity Monitor for Hadoop-based systems

IBM BA Software Practice Accelerator Program Leveraging IBM s Technical Strength

Insights into Enterprise Telecom Expense Management

IBM Sales and Distribution IBM and Manhattan Associates

IBM SPSS Modeler Premium

How To Create An Insight Analysis For Cyber Security

Afni deploys predictive analytics to drive milliondollar financial benefits

A business intelligence agenda for midsize organizations: Six strategies for success

The IBM Solution Architecture for Energy and Utilities Framework

Minimize customer churn with analytics

Leveraging innovative security solutions for government. Helping to protect government IT infrastructure, meet compliance demands and reduce costs

IBM Content Analytics adds value to Cognos BI

Spend Enrichment: Making better decisions starts with accurate data

IBM Global Business Services Microsoft Dynamics CRM solutions from IBM

IBM Executive Point of View: Transform your business with IBM Cloud Applications

The IBM Cognos family

IBM Security QRadar Risk Manager

Move beyond monitoring to holistic management of application performance

Taking control of the virtual image lifecycle process

Transcription:

Predictive Maintenance for How to prevent asset failure, control maintenance costs and anticipate budget needs Highlights Predictive maintenance helps government agencies automatically detect equipment failure patterns and predict future maintenance costs, so they can gain more value and uptime from assets, negotiate better service level agreements and plan for future budget appropriations. In this white paper, you ll learn the basics of predictive maintenance, the specific benefits it provides and the underlying technologies that make it possible. Faced with shrinking budgets, limited resources and increased citizen expectations for the quality and availability and of services, government agencies are under intense pressure to gain more value and usability from their assets. In response to these challenges, many public officials are seeking new ways to minimize unexpected equipment failure, anticipate maintenance costs, manage maintenance, repairs and operations (MRO) inventory, and negotiate the most beneficial service level agreements with vendors. Whether it s ensuring the combat readiness of war planes in military conflict zones, keeping public transportation and police department fleets up and running, or identifying the root cause of public utility equipment failures that contribute to power outages or flooding, there is an urgency at all levels of government to find more cost-effective solutions. Over the years, federal, state and municipal governments have developed a number of different approaches for keeping their assets up and running and on budget. Today many forward-looking agencies rely on predictive maintenance to go beyond the guesswork and inaccuracy of those traditional methods. Driven by predictive analytics, this leading-edge capability is helping those agencies save money by avoiding asset failure, eliminating unnecessary maintenance and providing superior budget forecasting by predicting the end of life for assets. In this white paper, you ll learn the basics of predictive maintenance for government entities, the specific benefits it can provide for your organization and the underlying technologies that make it possible.

Business Benefits Predictive maintenance enables government agencies to: Predict the reliability of assets in real time Plan future budget appropriations for asset maintenance and replacement Avoid the consequences of unexpected asset failure Predictive maintenance in action Aircraft Manufacturer A leading aircraft manufacturer used predictive maintenance to provide the lowest flight-hour cost and highest aircraft availability for its government clients. With the ability to predict repairs and associated costs for each aircraft, it can effectively anticipate government needs for their helicopter fleets. Predictive analytics: A game changer for government The basis of predictive maintenance is powerful predictive analytics software, which gathers and analyzes information from a variety of sources, including maintenance logs, performance logs, monitoring data, inspection reports, environmental data and financial data. The software detects even minor anomalies or failure patterns from this structured and unstructured data to determine the areas of greatest risk. It then generates alerts and recommended best actions which are integrated into workflow processes or delivered directly to decision-makers. Resources are then directed toward those areas before risk becomes reality. This early identification of maintenance requirements and operational issues is critical for preventing equipment failure, improving asset usability, forecasting future budget requirements and negotiating service level agreements with outsourcers. In this way, predictive maintenance can deliver sizable cost savings, increased operational efficiency, longer asset continuity and higher levels of satisfaction among the government personnel who depend upon these assets to perform their jobs. Most importantly, it enables a much higher level of reliability for equipment that safeguards the well-being and even the lives of citizens such as emergency vehicles, water treatment facilities, road construction equipment, disaster alert systems and other public health and safety assets. Now let s take a closer look at the three areas where predictive maintenance delivers the most significant benefits for government: field level maintenance, outsourcing relationships and budget forecasting.

Predictive maintenance in action National Military Agency A large national military agency used predictive maintenance on one of its warships to determine which equipment parts were likely to fail in the near future. By proactively replacing those parts during a scheduled port call, the ship avoided costly unexpected equipment downtime, which would have taken a great deal of time and personnel resources to remedy. Predictive maintenance for field level maintenance Performing timely maintenance is critical to preventing failures that may result in costly service interruptions, but relying on a fixed schedule may result in higher than necessary costs for both parts and labor. Predictive maintenance leverages a wide range of data that may include equipment type, number of days in operation, operating voltage, days from last service, days to next service, failure history, costs for planned and unplanned maintenance, parts analysis and other data depending upon the equipment involved. Predictive models are deployed which analyzes this data and identifies risks in real time based on previous events and process anomalies. If a failure does occur, advanced root cause analysis determines the source of the problem so you can correct the root cause and prevent these events in the future. Because you have 24/7 access to the reliability of every piece of equipment, you can evaluate the current status of all assets and build a maintenance schedule that performs inspections and/or maintenance just in time to prevent failures. This eliminates the cost and labor of performing regularly scheduled maintenance that may not be really necessary. In addition, when regularly scheduled maintenance is underway, you will know which parts may fail in the near future and replace them to further reduce future out of service time. As operating conditions change, the reliability of your assets is updated in real time. The advanced algorithms contained in the predictive maintenance software can determine the future reliability of assets so that inspections and maintenance can be performed at the optimal and most cost-effective moment. Predictive maintenance also identifies the replacement parts required to support this highly accurate maintenance schedule and eliminates the need for unnecessary and expensive overstocking of spare parts.

Predictive maintenance in action European Military Defense Agency A large European military defense organization used predictive maintenance to ensure the high availability of 150,000 spare parts that were critical to the maintenance of its fleet of planes. By analyzing technical risks, logistics, financial risks, economic conditions, and predicting future needs, the organization optimized its supply chain for more efficient and cost-effective plane maintenance. Predictive maintenance for outsourced service level agreements Of course, much of the asset and equipment maintenance within government agencies is performed by outsourced vendors. The challenge for those agencies is determining whether the vendor s service level agreement provides the most value and highest returns for the covered asset. The lack of complete and well-defined contractual terms for outsourced maintenance is a common source of cost-overruns and service interruptions for equipment that may be critical to an agency s responsibilities. Predictive maintenance offers direct insight into this process. By performing a complete analysis of historical trends and published manufacturer warranty terms, it can help you negotiate the most cost-effective SLA terms with your outsourcing provider. You are able understand when the asset will likely fail and require maintenance, when it will likely need replacement parts and the availability of those parts, as well when it will reach end of life. By negotiating a service level agreement based on predictive maintenance, you can reduce service costs, minimize downtime and gain more value over the life of each asset. Some government agencies may even require that their vendors invest in a predictive maintenance solution that helps them prevent unexpected equipment failure and provide more cost-effective maintenance services. The benefits of this technology can be then be distributed between both the agency and the outsourced vendor.

Predictive maintenance for budget forecasting In addition to reducing costs, another benefit of predictive maintenance that offers a dramatic impact for government agencies is the ability to accurately anticipate future expenses. By using analytics to predict future maintenance costs, the need for replacement parts, the likelihood of asset failure and the timeline for asset end of life, agencies can successfully forecast long-term spending and the need for appropriations in upcoming budgets. In this way, predictive maintenance helps government finance departments take control of costs and be prepared for the eventual replacement of assets. With early identification of potential equipment downtime, they can also lower the risk of unexpected failures in the field and the resulting loss of additional resources required to fill gaps should that occur. By proactively taking actions that prevent asset failure and using predictive analysis to plan for future budgetary needs, predictive maintenance acts as powerful fiscal tool for government agencies. IBM SPSS predictive maintenance technologies IBM SPSS predictive analytics provide powerful, proven predictive maintenance capabilities for government. By combining data from disparate sources and automatically detecting failure patterns, it enables the pre-emptive deployment of maintenance and repair resources in order to dramatically reduce downstream costs. With IBM SPSS predictive analytics, government agencies can predict the reliability of assets in real time, accurately forecast the end of life for assets, and anticipate future maintenance requirements in order to more effectively conduct budget planning and negotiate service level agreements with vendors. Across all types of assets and equipment, IBM SPSS predictive analytics helps government officials: Gain more value and service uptime from assets Identify when equipment is likely to fail or require maintenance Successfully negotiate SLA terms and conditions Ensure replacement parts are available when needed Plan for future budget appropriations Avoid the costs and consequences of unexpected asset failure

Conclusion As governments face increasing pressures to control costs and gain the highest levels of uptime for equipment and assets, predictive maintenance is emerging as a critical capability. Supported by predictive analytics, predictive maintenance empowers agencies to minimize unexpected equipment failure, anticipate the costs of maintenance, manage replacement parts inventory, and negotiate the most beneficial service level agreements with vendors. To find out how IBM SPSS predictive analytics can help your agency achieve the benefits of predictive maintenance, please call 800.543.2185.

About IBM IBM software delivers complete, consistent and accurate information that decision-makers trust to improve business performance. A comprehensive portfolio of business intelligence, predictive analytics, financial performance and strategy management, and analytic applications provides clear, immediate and actionable insights into current performance and the ability to predict future outcomes. Combined with rich industry solutions, proven practices and professional services, organizations of every size can drive the highest productivity, confidently automate decisions and deliver better results. As part of this portfolio, IBM SPSS Predictive Analytics software helps organizations predict future events and proactively act upon that insight to drive better business outcomes. Commercial, government and academic customers worldwide rely on IBM SPSS technology as a competitive advantage in attracting, retaining and growing customers, while reducing fraud and mitigating risk. By incorporating IBM SPSS software into their daily operations, organizations become predictive enterprises able to direct and automate decisions to meet business goals and achieve measurable competitive advantage. For further information or to reach a representative visit www.ibm.com/spss.

Copyright IBM Corporation 2011 IBM Corporation Route 100 Somers, NY 10589 US Users Restricted Rights - Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Produced in the United States of America March 2011 IBM, the IBM logo, ibm.com, WebSphere, InfoSphere and Cognos are trademarks or registered trademarks of International Business Machines Corporation in the United States, other countries, or both. If these and other IBM trademarked terms are marked on their first occurrence in this information with a trademark symbol ( or TM ), these symbols indicate U.S. registered or common law trademarks owned by IBM at the time this information was published. Such trademarks may also be registered or common law trademarks in other countries. A current list of IBM trademarks is available on the Web at Copyright and trademark information at www.ibm.com/legal/copytrade.shtml. SPSS is a trademark of SPSS, Inc., an IBM Company, registered in many jurisdictions worldwide. Other company, product or service names may be trademarks or service marks of others. P25930 Please Recycle YTW03156-USEN-00