{"title":"A RAMS Journey for MicroTurbine Power Generation","authors":"Evan Franke, Gérard Cohen","doi":"10.1109/RAMS48030.2020.9153587","DOIUrl":null,"url":null,"abstract":"When considering Reliability, Availability, Maintainability and Safety (RAMS) for a technically advanced device like Capstone’s microturbine power generator, we needed to explore many facets of its function, application, field location and operational performance. These variables became even more challenging when product installations took on a global scale and included various challenging and often isolated locations (oil platforms, landfills, remote islands, and more). Our RAMS journey for microturbines contains helpful guidance for any companies seeking a roadmap of how to incorporate reliability and availability analytics and principles into the fabric of their organization, especially through the early phases of company maturity.For early product development and initial launch, we used mean time between failures (MTBF) and Failure Rate (Lambda) as straightforward metrics for goal-setting and prioritizing improvement programs. A FRACAS database was used for collecting post-shipment data, and was essential for providing raw data for our analytics. We also began identifying technical staff that were talented in customer communication, who quickly became critical customer satisfaction champions during problem identification and resolution activities.As our product design stabilized, we began measuring customer service aspects such as response time and repair times, which we combined with reliability metrics to provide estimates of Availability. In order to capture the best-rounded understanding of the product RAMS performance, we looked at Availability metrics across different regions and markets, with each illuminating different challenges. Using Availability also provided a single metric that aligned our organization toward customer satisfaction by identifying how all employees could play a direct role in reliability and service improvement, regardless of their functional department.As our product fleet and customer base continues to grow and globalize, we are now engaging with our distribution business parmers to ensure that they adopt our culture and principles of customer satisfaction, as they are increasingly the face of our product to our end users. To this end, we use tools such as Key Performance Indicators (KPIs) and “model behaviors” to align and clarify roles and responsibilities between our companies, and to hold our business partners accountable for their role in customer satisfaction.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Annual Reliability and Maintainability Symposium (RAMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RAMS48030.2020.9153587","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
When considering Reliability, Availability, Maintainability and Safety (RAMS) for a technically advanced device like Capstone’s microturbine power generator, we needed to explore many facets of its function, application, field location and operational performance. These variables became even more challenging when product installations took on a global scale and included various challenging and often isolated locations (oil platforms, landfills, remote islands, and more). Our RAMS journey for microturbines contains helpful guidance for any companies seeking a roadmap of how to incorporate reliability and availability analytics and principles into the fabric of their organization, especially through the early phases of company maturity.For early product development and initial launch, we used mean time between failures (MTBF) and Failure Rate (Lambda) as straightforward metrics for goal-setting and prioritizing improvement programs. A FRACAS database was used for collecting post-shipment data, and was essential for providing raw data for our analytics. We also began identifying technical staff that were talented in customer communication, who quickly became critical customer satisfaction champions during problem identification and resolution activities.As our product design stabilized, we began measuring customer service aspects such as response time and repair times, which we combined with reliability metrics to provide estimates of Availability. In order to capture the best-rounded understanding of the product RAMS performance, we looked at Availability metrics across different regions and markets, with each illuminating different challenges. Using Availability also provided a single metric that aligned our organization toward customer satisfaction by identifying how all employees could play a direct role in reliability and service improvement, regardless of their functional department.As our product fleet and customer base continues to grow and globalize, we are now engaging with our distribution business parmers to ensure that they adopt our culture and principles of customer satisfaction, as they are increasingly the face of our product to our end users. To this end, we use tools such as Key Performance Indicators (KPIs) and “model behaviors” to align and clarify roles and responsibilities between our companies, and to hold our business partners accountable for their role in customer satisfaction.