This is a multi part project. Please read the first two part of the project and then work on assignment number 3.
1.Improvement Project (Kaizen Event) – This kaizen event or improvement project does not need to address all issues found in Assignment 2, but students are expected to coordinate and implement at least one kaizen or improvement to this process to tackle some of issues analyzed in Assignment 2. Follow this template to document this mini-kaizen event (Improvement Project (Kaizen Event) Template). This template includes some example entries to help students understand how to use it, as well as state a kaizen objective, ideal conditions, brainstorming potential actions (apply the lessons to this project), and prepare an implementation plan for this mini-kaizen event. Students should follow the steps on this template and edit the entries to support their own improvement project using this template (the action items from the course lessons provide further information to support this assignment).
·Students will develop a master improvement plan in Assignment 4 for additional improvements (beyond the scope of this class). While brainstorming improvement alternatives now some options may not fit this time period, but be good considerations for Assignment 4.
2.Review Impact – Students need to plan enough time to complete this kaizen event or improvement project in order to have time to measure the impact the improvement(s) had on the 3 process measures defined in Assignment 1. These 3 future metrics or measures should clearly show the impact these changes or improvements had on the performance of this process. Students need to structure 3 impact statements supporting these measures (see example on the template).
3. Identify Lessons Learned – Include challenges and experiences while doing this assignment. Generalize what you learned for use in later process improvement projects.
Treatment reception process is Assignment #1
Waste Audit is assignment #2 (keep in mind I didn’t get the best grade on that cause I was missing a lot of data)
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