Casestudie Breakdown prediction Contell PILOT - Transumo

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Therefore, statistical and data mining methods shall be applied to currently available datasets. Hence, existing customer data has to be collected and analyzed. Furthermore, above mentioned methods have to be evaluated on their feasibility to offer additional decision support and to reliably predict malfunctions. This study will stick to the data currently monitored by sensors in the field and will add no new measurement data. Moreover, it is necessary to point out the increase in value for the customer for the found solutions. First step of research is to define what monitoring is about and to explain its general importance, current practice, existing problems and a requirements analysis of a monitoring system within the setting of sensor based temperature monitoring of fridges. This is done in chapter 2. Afterwards a review of XiltriX and other major monitoring products is given in chapter 3 to point out the level of compliance with the worked out requirements. The succeeding chapter 4 will review the current state of research. Based on these results in combination with literature research, chapter 5 introduces suggestions, in which way the system could be improved. Aimed results are: 1. To gain additional knowledge of the cooling device’s condition from recorded datasets to offer additional decision support in case of an exceptional temperature level 2. To offer a software that reliably predicts upcoming malfunctions Offering additional knowledge to the customer, regarding the equipment’s condition, leads to the idea to determine, what important information could be retrieved from currently recorded datasets. Therefore, statistical and data mining methods are evaluated on being able to offer additional information. This evaluation contains questions like: • Which statistical methods can be applied? • What knowledge gain do they offer? • What are the benefits for the operational staff? A determination whether the possible knowledge gain is sufficient to also reliably predict upcoming malfunctions and a succeeding case study will conclude this study. 2
2 Sensor Based Temperature Monitoring This diploma thesis focuses on sensor based temperature monitoring of freezers and fridges within medical laboratories. Due to the functioning of a fridge and insufficient data of a high quantity of possible external influences, this setting is faced with particular problems. The Dutch company <strong>Contell</strong>/IKS supported this thesis by providing a lot of information about their sensor based monitoring system XiltriX. Moreover, <strong>Contell</strong>/IKS rendered interviews with several employees of the UMC St. Radboud (University hospital of Nijmegen, the Netherlands) possible. This customer also provided stored historical data, which enables a validation of promising analyzing methods. Based on the interview’s results, this chapter will highlight the importance of sensor based temperature monitoring of cooling devices within medical laboratories. Furthermore, typical behaviors of cooling devices as well as currently applied monitoring methods are introduced. The identification of possible problems and a requirements analysis for a perfect working monitoring system conclude this chapter. 2.1 Importance of Temperature Monitoring within Medical Laboratories As already pointed out in the last chapter, sensor based temperature monitoring becomes increasingly important within many different settings. Its task is to reliably determine the condition of monitored devices. In general, a monitored device should meet the following criteria to be classified as OK [Weerdesteyn06]: 1. Current state is within predefined specifications 2. General behavior did not change significantly on the short-run 3. General behavior did not change significantly on the long-run 4. Presumably the behavior will not change significantly in the future Such a classification is very important, because a lot of medical goods have to be kept cool. Blood samples, for example, need a constant temperature of about 6°C. Changes in temperature for a longer time are dangerous to these blood samples. Even more critical are cryogenic fridges. Their samples are stored at -80°C or even cooler. A freezer’s malfunction can destroy these samples within a very short time. That has to be avoided because most of them are part of research work and irrecoverable. The contents of a fridge normally range in age from a few days to more than thirty years. That is why a breakdown of a freezer can lead to a loss of more 3
Page 1 and 2: Technische Universität Braunschwei
Page 3 and 4: 4.4 Review of Current State of Rese
Page 5 and 6: Index of Tables Table 2-1: Error of
Page 7: 1 Introduction 1.1 Initial Position
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Page 25 and 26: 3 Current Monitoring Systems The la
Page 27 and 28: device’s condition. Especially th
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Page 31 and 32: To indicate important events within
Page 33 and 34: 1. Display stored data in table for
Page 35 and 36: This way of visualizing data is the
Page 37 and 38: free text. Moreover it is possible
Page 39 and 40: dependent limit and delay settings,
Page 41 and 42: Aside from these functions, the kin
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Page 45 and 46: alarms by the use of additionally a
Page 47 and 48: The third mentioned Centron Environ
Page 49 and 50: 4 Current State of Research As alre
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• Critical values • Pre-warning
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5 Possible and Promising Ways of Da
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could be: “The mean increase of a
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The mode is the most frequent value
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Figure 5-1: Two Samples of Regressi
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5.4.2 The Major Problems of Regress
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The next section will introduce tim
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explained in section 5.4. If such a
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pictured in Formula 5-12. Beside a
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P ( m) = P ( r ) ⋅ P ( m−r ) wi
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But the greatest problem is again t
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clustering as well as an analysis o
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The general idea of supervised lear
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sometimes data of a door opening se
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Beside the introduced notification
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A classification could be achieved
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Table 5-1: Estimated Improvements A
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As all these software products fail
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6.2 Case Study The UMC St. Radboud
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Figure 6-3: Maximum Values at Dayti
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Figure 6-5: Minimum Values at Dayti
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Figure 6-9: Standard Deviation at D
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Table 6-3: Reported Notifications (
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Important for the determination of
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Remarkable is a comparison to the a
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Interviews with several employees f
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7 Summary Cooling devices within me
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Bibliography Books and Articles: [B
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[Wittenberg98] Reinhard Wittenberg,
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Appendix 1 - Implementation of Inte
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%Name and location of the source fi
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Appendix 2 - Implementation of Stat
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dailydate = [dailydate; floor(date(
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%Count Dooropenings per Day dailydo
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xlswrite(strcat(path, 'Excel\', fil
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print('-dtiff', strcat(path, 'Graph
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ar([dailydate(1):dailydate(length(s
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Appendix 3 - Implementation of Data
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Duration = 0; maxtemp = 0; elseif (
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%Contains [Duration, Number of Occu
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disp(strcat('Dooropening
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