{"title":"Review in Maintenance Strategies for Haemodialysis Machine in Healthcare Facilities","authors":"D. Mutia, L. Mukhongo, P. Chemweno","doi":"10.11648/J.IE.20180201.15","DOIUrl":null,"url":null,"abstract":"Hemodialysis machines are critical medical equipment in healthcare facilities for renal replacement therapy in form of dialysis treatment on solving chronic kidney diseases in Sub Sahara Africa. It is a vital machine which acts as human kidney by incorporating electromechanical controlled extracorporeal blood paths that leverage pumps and semi permeable dialyzer membranes to filter the patient’s blood. The biggest challenge to the biomedical engineers in most African hospitals is to maintain the manufacturer’s safety and performance specification of the haemodialysis equipment. There is a need for effective maintenance strategy for haemodialysis medical equipment in order to maintain the manufacturer’s set specification to meet clinical expectations and hence improve its reliability. The overall goal of the research paper is therefore to analyze the influence of different maintenance strategies and subsequently improve on the reliability of hemodialysis equipment in healthcare institutions in Kenya. The research will prioritize hemodialysis machine as critical medical equipment and use comprehensive secondary data to review and analyze the strategic maintenance applied in health institutions to optimize the best and cost effective strategic maintenance for the hemodialysis medical equipment. The ant colony optimization (ACO) algorithms may be less expert reliant and avoid uncertainty and ambiguity to determine the best strategic maintenance management to manage hemodialysis medical equipment in the hospitals. The results will provide an opportunity to technical engineers to develop a predictive and intelligent management system in the hospitals to minimize or remove the Mean Downtime (MDT) and Mean time to repair (MTTR) for a failed hemodialysis machines and improve the reliability of the hemodialysis machine.","PeriodicalId":54988,"journal":{"name":"Industrial Engineer","volume":"34 1","pages":"34"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrial Engineer","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/J.IE.20180201.15","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
Hemodialysis machines are critical medical equipment in healthcare facilities for renal replacement therapy in form of dialysis treatment on solving chronic kidney diseases in Sub Sahara Africa. It is a vital machine which acts as human kidney by incorporating electromechanical controlled extracorporeal blood paths that leverage pumps and semi permeable dialyzer membranes to filter the patient’s blood. The biggest challenge to the biomedical engineers in most African hospitals is to maintain the manufacturer’s safety and performance specification of the haemodialysis equipment. There is a need for effective maintenance strategy for haemodialysis medical equipment in order to maintain the manufacturer’s set specification to meet clinical expectations and hence improve its reliability. The overall goal of the research paper is therefore to analyze the influence of different maintenance strategies and subsequently improve on the reliability of hemodialysis equipment in healthcare institutions in Kenya. The research will prioritize hemodialysis machine as critical medical equipment and use comprehensive secondary data to review and analyze the strategic maintenance applied in health institutions to optimize the best and cost effective strategic maintenance for the hemodialysis medical equipment. The ant colony optimization (ACO) algorithms may be less expert reliant and avoid uncertainty and ambiguity to determine the best strategic maintenance management to manage hemodialysis medical equipment in the hospitals. The results will provide an opportunity to technical engineers to develop a predictive and intelligent management system in the hospitals to minimize or remove the Mean Downtime (MDT) and Mean time to repair (MTTR) for a failed hemodialysis machines and improve the reliability of the hemodialysis machine.