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WRIGHT-PATTERSON AIR FORCE BASE, Ohio (AFNS) -- ' + '' + ' '; } else { caption += $(this).find('figcaption').html() + getDetailsURL($(this).parent()) + getDownloadURL($(this).parent()) + showFBShare(); } } return caption; }, afterLoad: function (instance, current) { //initial desktop view if (isMobile()) $(".fancybox-caption__body").addClass("mobile"); }, afterShow: function (instance, current) { var $currentSlide = $(".fancybox-slide.fancybox-slide--current.fancybox-slide--image").parent().parent(); if (isMobile()) $currentSlide.find(".fancy-detail-link").on("touchstart", function() { captionToggle(); }); }, afterClose: function () { } })); let debounceTimer; $(window).on("resize", function (event) { if (isMobile()) return; if ($(".af3-caption-body").length > 0 && $(".af3-caption-body").css("height") != undefined) { event.stopImmediatePropagation(); $(".fancybox-caption__body").removeClass("half"); isDesktopInit = false; captionToggle(); debounceTimer = setTimeout(function () { clearTimeout(debounceTimer); debounceTimer = null; recalculateImageSize(); }, 1000); } }); function recalculateImageSize() { // Fancy box miscalculates because of race conditions with new layout var origImgWth = $(".fancybox-image").prop("naturalWidth"); var origImgHgt = $(".fancybox-image").prop("naturalHeight"); var winWth = $(window).innerWidth(); var winHgt = $(window).innerHeight() var ratio = Math.min(winWth / origImgWth, winHgt / origImgHgt); var newImgWth = (origImgWth * ratio); var newImgHgt = (origImgHgt * ratio); var dstTop = Math.floor((winHgt - newImgHgt)) / 2; var dstLeft = Math.floor((winWth - newImgWth)) / 2; $(".fancybox-content").removeAttr("style"); $(".fancybox-content").css("width", newImgWth + "px"); $(".fancybox-content").css("height", newImgHgt + "px"); $(".fancybox-content").css("transform", "translate(" + dstLeft + "px, " + dstTop + "px)"); } function captionToggle() { if ($(".fancybox-caption__body").hasClass("af3-caption-body")) { $(".af3-caption-body").stop(true, false).animate({ height: "0vh" }, 800, function () { // Animation complete. closeDetails(); }); $(".fancy-photo-detail-link").html($(".fancy-photo-detail-link").html().replace("CLOSE", "SHOW")); } else { $(".fancybox-caption__body").addClass("af3-caption-body"); $(".af3-caption-body").addClass(detailSize); $(".af3-caption-body").animate({ height: displayhgt }, 800); $(".fancybox-caption").addClass("af3-caption-bg"); $(".base-caption-info").addClass("full-height"); $(".fancy-photo-detail-link").addClass("photo-detail-gradient"); $(".fancybox-button").css("display", "none"); $(".fancy-photo-detail-link").html($(".fancy-photo-detail-link").html().replace("SHOW", "CLOSE")); $(".fancybox-caption__body").prepend(prependClosing()); $(".closing-box, .closingx").on("touchstart", function() { captionToggle(); }); } } function getDetailsURL(fbObj) { return 'DETAILS'; } function getDownloadURL(fbObj) { return 'DOWNLOAD'; } function showFBShare() { return 'SHARE'; } function closeDetails() { $(".af3-caption-body").removeClass(detailSize); $(".fancybox-caption__body").removeClass("af3-caption-body"); $(".fancybox-caption").removeClass("af3-caption-bg"); $(".base-caption-info").removeClass("full-height"); $(".fancy-photo-detail-link").removeClass("photo-detail-gradient"); $(".fancybox-button").css("display", "block"); if (detailSize === "half") { detailSize = "full"; displayhgt = "90vh"; $(".fancybox-caption").removeClass("desktop-init"); } } function prependClosing() { return '' } function isMobile() { var isMobile = false; //initiate as false // device detection if (/(android|bbd+|meego).+mobile|avantgo|bada/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|ipad|iris|kindle|Android|Silk|lge |maemo|midp|mmp|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)/|plucker|pocket|psp|series(4|6)0|symbian|treo|up.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino/i.test(navigator.userAgent) || /1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw-(n|u)|c55/|capi|ccwa|cdm-|cell|chtm|cldc|cmd-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc-s|devi|dica|dmob|do(c|p)o|ds(12|-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(-|_)|g1 u|g560|gene|gf-5|g-mo|go(.w|od)|gr(ad|un)|haie|hcit|hd-(m|p|t)|hei-|hi(pt|ta)|hp( i|ip)|hs-c|ht(c(-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i-(20|go|ma)|i230|iac( |-|/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |/)|klon|kpt |kwc-|kyo(c|k)|le(no|xi)|lg( g|/(k|l|u)|50|54|-[a-w])|libw|lynx|m1-w|m3ga|m50/|ma(te|ui|xo)|mc(01|21|ca)|m-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|-([1-8]|c))|phil|pire|pl(ay|uc)|pn-2|po(ck|rt|se)|prox|psio|pt-g|qa-a|qc(07|12|21|32|60|-[2-7]|i-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55/|sa(ge|ma|mm|ms|ny|va)|sc(01|h-|oo|p-)|sdk/|se(c(-|0|1)|47|mc|nd|ri)|sgh-|shar|sie(-|m)|sk-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h-|v-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl-|tdg-|tel(i|m)|tim-|t-mo|to(pl|sh)|ts(70|m-|m3|m5)|tx-9|up(.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas-|your|zeto|zte-/i.test(navigator.userAgent.substr(0, 4))) { isMobile = true; } return isMobile; } });The Air Force Rapid Sustainment Offices Predictive Analytics and Decision Assistant leverages artificial intelligence software to transform logistics data into actionable predictive maintenance alerts. The Air Force has designated PANDA as the System of Record for Condition Based Maintenance Plus and predictive maintenance, the first such designation for the RSO.

CBM+ is a collaborative Department of Defense readiness initiative focused on data analysis to improve availability and lifecycle cost. CBM+ requires advanced tools and technologies for analysis to formulate evidence of need to perform maintenance.

Developed by the RSO and partner, C3.ai, PANDA is an artificial intelligence software toolkit that delivers integrated and interoperable tools, technologies, and information infrastructures to facilitate CBM+ collaboration across multiple functional and organizational boundaries. It maximizes the use of common equipment and technologies to capture, store, analyze, and forward CBM+ predictive maintenance data. PANDA has rapidly expanded to the maintenance operations of 16 aircraft platform communities across all nine Air Force major commands. PANDA routinely generates over 30,000 predictive maintenance recommendations and sensor-based alerts detecting impending component failure.

PANDA being designated as the Air Forces system of record for CBM+ is a monumental achievement for the RSO and Air Force CBM+ enterprise, said Chris Damani, RSO CBM+ Program Office chief. Alignment to one technology solution unites the sustainment enterprise to one tool and brings focus, dedication, and prioritization of resources to PANDA allowing for further expansion, optimization, and impact to mission readiness.

The RSO CBM+ Program Office is the Air Forces CBM+ Center of Excellence leading the implementation and execution of CBM+ across the Air Force. The office will now lead and manage all Air Force CBM+ initiatives interested in integration into the PANDA platform, which is expandable to all Air Force materiel categories, including aircraft, missiles, and support equipment and vehicles.

The future of Air Force predictive maintenance is now, and PANDA is the Air Force System of Record helping to lead the way.

Learn more about PANDA:

Read more here:
Rapid Sustainment Office's CBM+ artificial intelligence toolkit earns ... - Air Force Link