Defects reporting data inconsistency reduced by 80 percent. Field personnel were unable to update their tasks or sync data with the host system. User satisfaction and acceptance of the TMS increased tremendously. This expedited the resolution process by 20 percent.
It was suggested that implementing a more sophisticated load-balancing technique between the servers may help to reduce the load on the existing servers, improve system stability and prevent user requests from getting bottlenecked.
Vetting of defect reports.
The input-process-output IPO tool was used to winnow down the factors that affect the resolution time of defects. Resolution Time of Defects Slow response times were addressed with a 5 Whys analysis, which revealed the following issues as causes for delays: Verbiage and input format was standardized.
All tickets coming to IT had all the required information on them, and were accompanied by screen shots.
The average resolution time of incidents was approximately 20 minutes. The requests to the servers could be processed in the order in which they were received.
These simple procedures expedited the speed of defect resolution. There was no time wasted in contacting the user and gathering important information. The stability and availability of the system improved tremendously and downtime was reduced from an average of 20 minutes to less than one minute.
In order to trace the root cause of these slow and stopped periods, message queues and server logs were analyzed. User training was provided where needed.
The team turned to lean and the Red X approaches they use to solve vehicle performance issues to increase their output of completed projects by making the problem-solving process more efficient. As a result of this project, branch and field personnel no longer worry about system availability and data inconsistency; instead, they can focus on their jobs.
The group was one of three teams to earn a silver medal in the International Team Excellence Competition. Within two years after landing his first job, he received two promotions and tripled his salary. Detailed documentation and quantitative analysis of system downtimes ensured that the decision to implement load-balancing for the TMS was escalated and prioritized.
Defects Reported in the TMS Poor system availability, or downtime, accounted for approximately 34 percent of all reported defects, making it the primary issue facing field personnel.
By defining and then standardizing key processes, the unit minimized variation, shared best practices, and sustained improvements. The simplistic round-robin domain name system load balancing that was already in use was not sufficient to ensure that the system was available at all times.
A Six Sigma improvement team used quality tools including trend charts, Pareto charts, and cause-and-effect diagrams to analyze the failure modes for the reported defects, finding that many were not being covered by product testing processes.problem or rejection criteria facing by a manufacturing company.
The root A Case Study The application of Six-Sigma methodology is a statistical analysis approach to quality statistically using DMAIC methodology and suggestions for quality improvement will be made to the department.
A recent study of implementation of Six Sigma at Continental Mabor, a tire manufacturing company located in Famalicao, Portugal, provides a step-by-step look at putting Six Sigma’s DMAIC methodology into place.
A Six Sigma Case Study – Tutorial for IT Call Center – Part 1 of 6.
Application of DMAIC for Process Industry: A Case Study Vikas Kumar, mi-centre.com Scholar, HEC Jagadhri, Yamunanagar with minimum number of rejection in their manufacturing products.
For better improvement in application of Six Sigma methodology and Selection of tools. In the scope of Six Sigma methodology application for the existing manufacturing system, according to DMAIC cycle (Define-Measure-Analyse-Improve-Control), this paper presents case study.Download