Loggdata från webbservrar innehåller värdefull information om användares beteenden på en webbplats, och reflekterar i stort hur användare känner om webbplatsen. Genom att analysera loggdata går det att få en bra bild av användarupplevelsen, vilket i sin tur kan vägleda i förbättring av webbplatsen. För att underlätta dataanalys används interaktiv datavisualisering i form av till exempeldiagram, men visualiseringsverktyg behöver kunna användas flexibelt och i snabbtakt för att kunna vara praktiska. Problemet med att visualisera och analysera loggdata är dock att denna typ av data ständigt fortsätter att växa i storlek. Och vid visualisering av stora dataset kan renderingstiden påverkas. Tre JavaScript-bibliotek för visualisering jämförs utifrån renderingstider, dessa är D3.js, Google Charts och Chart.js. Ett tekniskt experiment utförs där de tre biblioteken jämförs mot varandra både vad gäller initial och interaktiv renderingstid. Resultatet tyder på att D3.js är mest lämpat för interaktiv visualisering av loggdata när det kommer till renderingstid.

Sig sigma is a methodology where companies strive to reproduce results ending up having a 99.9996% chance their product will be void of defects. In order for companies to reach six sigma, statistical process control (SPC) needs to be introduced. SPC has many different tools associated with it, control charts being one of them. Control charts play a vital role in managing how a process is behaving. Control charts allow users to identify special causes, or shifts, and can therefore change the process to keep producing good products, free of defects. There are many factories and manufacturing facilities having implemented some sort of statistical process control. St. Jude Medical implemented control charts to monitor different tools on the manufacturing line. How the data is entered and stored poses a difficult situation for the person monitoring the processes. The program used to keep the control charts is not user friendly and difficult to use. Another program can be produced to provide a greater level of efficiency. The goals of this project are to stress how important control charts are in the manufacturing world, what problems are currently seen for operators and supervisors, and how a new and improved program can help fix the current situation. This paper goes into the reasons for the change as well has what has been improved.

The appropriate selection of failure criterion for solder joint studies is necessary to correctly estimate reliability life. The objective of this study is to compare the effect of different failure criteria on the reliability life estimation. The four failure criteria in this study are a 20% resistance increase defined in the IPC-9701A standard, a resistance beyond 500 Ω, an infinite resistance (hard open), and a failure criterion based on X-bar and R control charts. Accelerated thermal cycling conditions of a low-silver BGA study included 0°C to 100 °C with ten minute dwell times and -40°C to 125°C with ten minute dwell times. The results show that the life estimation based on X-bar and R failure criterion is very similar to the life estimation when a 20% resistance increase defined in the IPC-9701A failure criterion is used. The results also show that the reliability life would be overestimated if the failure criterion of a resistance threshold of 500 Ω or an infinite resistance (hard open) is used.

When using control charts to monitor a process it is frequently necessary to simultaneously monitor more than one parameter of the process. Multivariate control charts for monitoring the mean vector, for monitoring variance-covariance matrix and for simultaneously monitoring the mean vector and the variance-covariance matrix of a process with a multivariate normal distribution are investigated. A variable sampling interval (VSI) feature is considered in these charts. Two basic approaches for using past sample information in the development of multivariate control charts are considered. The first approach, which is called the combine-accumulate approach, reduces each multivariate observation to a univariate statistic and then accumulates over past samples. The second approach, which is called the accumulate-combine approach, accumulates past sample information for each parameter and then forms a univariate statistic from the multivariate accumulations. Multivariate control charts are compared on the basis of their average time to signal (ATS) performance. The numerical results show that the multivariate control charts based on the accumulate-combine approach are more efficient than the corresponding multivariate control charts based on the combine-accumulate approach in terms of ATS. Also VSI charts are more efficient than corresponding FSI charts. / Ph. D.

Successfully implementing continuous improvement and quality methodologies have been challenging over the past century. Challenges occur in managing change in the organization, which can be effectively addressed through relationship building in concert with strong leadership. Even with solid leadership, change management, and relationship building, initiatives have challenges quantifying and identifying when to intervene in order to keep them on track for success. Creating a quantitative model using a 3-parameter logit s-curve, Blythe S-curve, to illustrate the growth and decay of the handoff of projects to the process owner will allow leadership the knowledge and direction to keep the initiative moving in a positive direction. Leveraging the Hotelling T2 multivariate charts on the residuals derived from the Blythe S-curve will give definitive statistical evidence on when to intervene on projects in the earliest possible time frame. Leaders in organizations implementing and actively using change management, relationship building, the Blythe S-curve model, and Hotelling T2 multivariate charts to drive quality and continuous improvement methodologies in their organization will improve the likelihood of success.

This document is a multiple-article format dissertation that discusses the iterative design, development, and evaluation processes necessary to create high quality learning analytics dashboard systems. With the growth of online and blended learning environments, the amount of data that researchers and practitioners collect from learning experiences has also grown. The field of learning analytics is concerned with using this data to improve teaching and learning. Many learning analytics systems focus on instructors or administrators, but these tools fail to involve students in the data-driven decision-making process. Providing feedback to students and involving students in this decision-making process can increase intrinsic motivation and help students succeed in online and blended environments. To support online and blended teaching and learning, the focus of this document is student-facing learning analytics dashboards. The first article in this dissertation is a literature review on student-facing learning analytics reporting systems. This includes any system that tracks learning analytics data and reports it directly to students. The second article in this dissertation is a design and development research article that used a practice-centered approach to iteratively design and develop a real-time student-facing dashboard. The third article in this dissertation is a design-based research article focused on improving student use of learning analytics dashboard tools.

This document is a multiple-article format dissertation that discusses the iterative design, development, and evaluation processes necessary to create high quality learning analytics dashboard systems. With the growth of online and blended learning environments, the amount of data that researchers and practitioners collect from learning experiences has also grown. The field of learning analytics is concerned with using this data to improve teaching and learning. Many learning analytics systems focus on instructors or administrators, but these tools fail to involve students in the data-driven decision-making process. Providing feedback to students and involving students in this decision-making process can increase intrinsic motivation and help students succeed in online and blended environments. To support online and blended teaching and learning, the focus of this document is student-facing learning analytics dashboards. The first article in this dissertation is a literature review on student-facing learning analytics reporting systems. This includes any system that tracks learning analytics data and reports it directly to students. The second article in this dissertation is a design and development research article that used a practice-centered approach to iteratively design and develop a real-time student-facing dashboard. The third article in this dissertation is a design-based research article focused on improving student use of learning analytics dashboard tools.

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