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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A study of sample entropy towards process capability

Zhang, Zheng January 1900 (has links)
Master of Science / Industrial & Manufacturing Systems Engineering / Shing I. Chang / The process capability is a measurable property of a process related to the specification of a product. Traditionally, process capability analysis (PCA) measurements are expressed by a process capability ratio (PCR). When using a typical PCR to measure process capability, there are certain assumptions, and critics have been made towards PCR, that some the assumptions are violated. Much research has been conducted to ratify the situations when some of the assumptions are violated. This thesis, is going to demonstrate a research towards process capability using Sample Entropy method. The desirable outcome would be that this method can avoid violating the assumptions.
2

Aplikace statistické regulace procesu na nový produkt / The aplication of the statistical process control on the new product

Ježková, Kateřina January 2008 (has links)
The thesis is concerned with the aplication of the statistical process control on the new product and it provides proposals to its improvement in Plastik, s.r.o.
3

Monitoring Safety Process Performance with Leading Indicator Safety Audits

Van Bibber, Ashley M. 17 September 2015 (has links)
No description available.
4

Ensuring high-quality production during commissioning and ramp-up : A case study at Northvolt

Eklund, Henrik, Engström, Jacob January 2021 (has links)
Rechargeable lithium-ion batteries (LIBs) have generated a shift in the automotive industry towards electric vehicles (EVs) instead of vehicles powered by fossil fuels. As a result, the demand for LIBs is only expected to grow in the future due to an increased demand for passenger EVs. Consequently, LIB manufacturers have to increase their production to meet the increasing demand. Northvolt is a Swedish LIB manufacturer founded in 2016, aiming to start the production of LIBs at the Northvolt Ett factory in Skellefteå during 2021. The Northvolt Ett factory will be one of the largest battery plants in Europe, supplying battery cells for both commercial and domestic use. Poorly manufactured battery cells can potentially cause hazardous events, such as fires or explosions, further supporting the need for high quality batteries. Consequently, requirements from customers and industry standards are high in terms of product quality control through e.g. measurement system analysis (MSA), statistical process control (SPC), and capability analysis. Furthermore, previous research has highlighted issues during commissioning and ramp-up of production, potentially occurring at Northvolt Ett.  The purpose of this study has been to describe how high-quality production can be ensured and maintained during and after commissioning. The study has been conducted as a qualitative case study at Northvolt Ett, focusing on qualification of the coating process. The basis for the study was to examine previous research on quality assurance from other industries, analyze automotive standards, and gather learnings from the pilot production at Northvolt Labs in Västerås. Unstructured interviews were conducted with Northvolt staff to understand what had previously been done related to quality assurance for Coating.  The learnings from Northvolt Labs highlighted a clear focus on preventive actions, such as establishing a Design-FMEA, Process-FMEA, and a Control Plan for the coating process. However, room for improvement was identified in terms of process improvement and control, since the lack of SPC has yielded unreliable results from the performed capability analysis. In addition, previous research has shown that preventive actions should be combined with actions for process improvement to reach full-scale production quickly. Thus, recommendations have been made for Northvolt to implement a clear strategy for product qualification through SPC and capability analysis, as a complement to the preventive actions. The recommendations include specific propositions for validation of the coating process and a general framework for process validation through MSA, SPC, and capability analysis. The presented recommendations can help Northvolt perform successful commissioning of the processes at Northvolt Ett and can also be useful for process validation in other manufacturing industries. / Laddningsbara litium-jon-batterier (LIB:s) har skapat en omställning i bilindustrin mot eldrivna fordon istället för fordon som drivs av fossila bränslen. Som en konsekvens väntas efterfrågan av LIB:s bara att öka i framtiden på grund av en ökad efterfrågan på eldrivna passagerarfordon. LIB-tillverkare måste därför öka sin produktion för att möta den växande efterfrågan. Northvolt är en svensk LIB-tillverkare som grundades 2016, med sikte på att starta produktionen av LIB:s vid fabriken Northvolt Ett i Skellefteå under 2021. Fabriken Northvolt Ett kommer att vara en av de största batterifabrikerna i Europa och leverera battericeller för både kommersiell och privat användning. Dåligt tillverkade battericeller kan potentiellt orsaka allvarliga händelser som bränder eller explosioner, vilket vidare stödjer behovet av batterier med hög kvalitet. Till följd av detta är kraven från standarder och tillverkare inom bilindustrin höga i termer av kvalitetskontroll av produkter genom t.ex. mätsystemanalys (MSA), statistisk processtyrning (SPS), och duglighetsanalys. Vidare visar tidigare forskning på problem som kan uppstå under driftsättning och upprampning av produktion, vilka potentiellt kan uppstå för Northvolt Ett.  Syftet med denna studie har varit att beskriva hur högkvalitativ produktion kan säkerställas och upprätthållas under och efter driftsättning. Studien har genomförts som en kvalitativ fallstudie vid Northvolt Ett med fokus på kvalifikation av coating-processen. Utgångspunkten för studien har varit att undersöka tidigare forskning inom kvalitetssäkring från andra industrier, analysera standarder från bilindustrin, och hämta in lärdomar från pilotproduktionen vid Northvolt Labs i Västerås. Ostrukturerade intervjuer genomfördes med anställda på Northvolt för att öka förståelsen för vad som tidigare gjorts relaterat till kvalitetssäkring för Coating.  Lärdomarna från Northvolt Labs visade ett tydligt fokus på förebyggande åtgärder, som upprättande av en Design-FMEA, Process-FMEA, och en kontrollplan för coating-processen. Dock identifierades ett förbättringsområde inom åtgärder för processförbättring och kontroll, då avsaknaden av SPS har genererat opålitliga resultat från den genomförda duglighetsanalysen. Vidare har tidigare forskning visat att förebyggande åtgärder borde kombineras med åtgärder för processförbättring för att snabbt uppnå fullskalig produktion. Rekommendationer har därför tagits fram till Northvolt för att implementera en tydlig strategi för produktkvalifikation genom SPS och duglighetsanalys, som ett komplement till de förebyggande åtgärderna. Dessa rekommendationer inkluderar specifika förslag för validering av coating-processen samt ett generellt ramverk för processvalidering genom MSA, SPS, och duglighetsanalys. De presenterade rekommendationerna kan hjälpa Northvolt att genomföra en framgångsrik driftsättning av processerna på Northvolt Ett och kan även vara användbara för processvalidering i andra tillverkningsindustrier.
5

Machine Learning Driven Simulation in the Automotive Industry

Ram Seshadri, Aravind January 2022 (has links)
The current thesis investigates data-driven simulation decision-making with field-quality consumer data. This is accomplished by outlining the benefits and uses of combining machine learning and simulation in the literature and by locating barriers to the use of machine learning (ML) in the simulation subsystems at a case study organization. Additionally, an implementation is carried out to demonstrate how Scania departments can use this technology to analyze their current data and produce results that support the exploration of the simulation space and the identification of potential design issues so that preventative measures can be taken during concept development. The thesis' findings provide an overview of the literature on the relationship between machine learning and simulation technologies, as well as limitations of using machine learning in simulation systems at large scale manufacturing organizations. Support vector machines, logistic regression, and Random Forest classifiers are used to demonstrate one possible use of machine learning in simulation.

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