pls answer task 1 in typing.

Q(1. -statistical quality control -acceptance sampling

process control chart(special cause

common cause) need to include all these facts for task 1. thanks

Unit Learning Outcomes: LO1: Illustrate the applications of statistical process control when applied in an industrial environment to improve efficiency. LO2: Analyse cost effective quality control tools. Assignment Brief and Guidance: Scenario: You have just joined Asia Electronics Manufacturing Services Pte Ltd as a Quality Engineer. The company manufactures electronics circuit boards for the automotive industry. You have immediately noticed that the quality control processes and procedures are not in place. This leads the company into great loss in revenue. Moreover, the company has received a lot of complaints from its customers affecting its image. After a quick conversation with your colleagues on the matter, they agree that this matter must be brought up to management. However, they do not know this subject well. They are not confident to convince the management. Activity: In this situation, you have decided to bring this matter up to management and convince them. So you will need to produce a report on the quality control situation in your company. The report has caught the attention of some managers in the company and one of them requests you to make a detailed analysis on the different quality control tools, techniques and provide any information on costing techniques. Task: 1) You determine that the best way to get this information across is to write a report to your managers discussing: The techniques used to support quality control, explain how these techniques could be used in this company environment, Describe the processes used in statistical process control for your company, also consider whereabouts these processes could be applied. With this in mind, give justified reasons as to why you would recommend the use of statistical process control within this engineering environment. Describe the differences between common cause and special cause variations in statistical process control