National Center for Manufacturing Sciences News and Views from the World of Manufacturing
March 2013 Welcome to The CTMA Connector, a monthly newsletter designed to provide news and ideas about the Commercial Technologies for Maintenance Activities (CTMA) program. The CTMA program is a joint Department of Defense/National Center for Manufacturing Sciences (DoD/NCMS) effort promoting collaborative technology development between industry and the DoD maintenance and repair facilities. This newsletter highlights ongoing projects, serves as a forum for promoting new project ideas, and provides other news of interest to the program. Our goal is to stimulate your participation and solicit your input.
Feel free to submit items for the newsletter as well as any suggestions to make it more useful. More information about the program can be found at http://ctma.ncms.org/.
To subscribe or unsubscribe to the CTMA Connector, send a message to: firstname.lastname@example.org with “subscribe CTMANewsletter” or “unsubscribe CTMANewsletter” in the message body.
Navy Yard Technology Showcase Postponed
Due to the budgetary uncertainties within the federal government, we have decided to postpone the April 9th NCMS/CTMA Technology Showcase at the Navy Yard until later this year. We apologize for any inconveniences this may cause to you.
Join us at the 2013 Annual CTMA Partners Meeting, May 21 through 23.
The CTMA Partners Meeting is a combination virtual, and networking event. Live keynote addresses and panel discussions will be via video-conference with rebroadcast over the internet to anyone registering for the event. Tune-in to the conference whenever you want.
Industry and local DoD personnel are invited to join us at NCMS in Ann Arbor for the Partners Meeting. Project teams will be showcased during the Meeting, and each team will have 30 minutes to present their technology for broadcast to participants throughout the sustainment community. We are also planning a networking reception on May 21 and lunch on the 22nd.
Thanks to all the teams submitting concept papers to this years Maintenance Challenge. Papers are currently being judged by the DoD evaluation team, and winners are expected to be announced in early April. The winning team will also be featured at the Annual Partners Meeting.
New NCMS Project: Collective Minds – Avoidance of Maintenance Cost through Predictive Trending
Fleets of aerospace equipment are managed through carefully controlled supply chain processes. When any of the planning assumptions fail, for example, due to a new mission, a batch of out-of-spec parts or an ill-conceived maintenance procedure, an unexpected demand on maintenance and supply can develop, leading to increases in operating costs and reductions of equipment availability. Isolation of early warning signals of onset of such crises is critical to dealing with them proactively. Complexities of aerospace fleets make it particularly difficult for managers to recognize emerging patterns of systematic failures before they escalate. Often, only when availability is significantly affected, will attention be paid.
Systematic failures of components in man-made fleets bear an analogy to disease outbreaks among humans. The spread of an out-of-spec parts from a delivery in some ways is like a new virus entering a community. Often, healthcare providers remain unaware of the system-wide nature of a problem until relatively late in its progression. Fortunately, data mining and machine learning technology has been demonstrated to reliably generate early warnings of the advent of human epidemics by observing the operation of the health care system over time.
This project will begin to explore the hypothesis that similar mathematics has value in alerting to unusual patterns when monitoring health of fleets of the US Army’s helicopter fleets with the goal of seeing whether multi‐year cost avoidance can be achieved at the enterprise level. This will be done by identifying high value analyses and relevant demonstrations with the current Army Aviation data that have the ability to scale across the DoD and enable explanation of variances in reliability calculations and demand forecasting so that proactive cost‐reducing actions may be taken across DoD.