Chat with us, powered by LiveChat To learn how to apply?Statistical Process Control Methods?(SPCM) to a process, continue the flowchart from Week 1 and identify variances within a process. You can find variances from - Writeden

  1. This assignmnet has a grading rubric

    To learn how to apply Statistical Process Control Methods (SPCM) to a process, continue the flowchart from Week 1 and identify variances within a process. You can find variances from the data identified in Week 1.

    Complete the Week 2 Statistical Process Control Methods Worksheet.

    To begin, measure the entire process over 10-12 periods of time (days, months, years). Use time as your Metric.
    Create a control chart including the baseline, upper control limits (UCL) and lower control limits (LCL). 

    Submit your assignment using the Week 2 Statistical Process Control Methods Worksheet.
    You may include your computations and graphs on the work sheet, or attach them separately.

     Use subject line of:
    Student Name, Assignment week, date due
    Example
    Michael Lindquist, Week 2, 5.23.2023

OPS/574 v1

Statistical Process Control Methods

OPS/574 v1

Page 2 of 2

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Statistical Process Control Methods

Process Evaluation

Evaluate your process using 1 of the following:

· Use the lean concept to find ways to eliminate waste and improve the process

· SPC or Six Sigma to reduce defects or variances in the process

<Write your evaluation here>

Evaluation of Control Chart and Process Metrics

Complete the following in Excel:

· Calculate the defined process metrics including variation and process capability.

· Develop and display a control chart for the process.

Evaluate the control chart and process metrics using Statistical Process Control (SPC) methods. Determine whether the process could benefit from the use of Six Sigma, Lean, or other tools. (Include all calculation and charts.)

<Write your evaluation here>

Executive Summary

Write a 700-word executive summary that includes the following:

· A summary of the Process Evaluation (using either Lean or SPC or Six Sigma)

· A summary of the Evaluation of Control Chart and Process metrics based on SPC methods

· A summary of your evaluation of whether the process would benefit from the use of Six Sigma, Lean, or other tools

· A description of the SPC project and recommendations for improvements

<Write your executive summary here>

Copyright 2020 by University of Phoenix. All rights reserved.

Copyright 2020 by University of Phoenix. All rights reserved.

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As-is Manufacturing Process flowchart for Apple company.

Gbenga Adeogun

University of Phoenix

OPS/574

May 16, 2023

Michael Lindquist

As-is Manufacturing Process flowchart for Apple company.

Distribution

Final quality control

Packaging

Assembly quality control

Assembly

Component quality control

Component manufacturing

Raw material inspection

Source raw material

The manufacturing procedure that is now used by Apple Company is comprised of numerous important phases. The procurement of raw materials is the first step, followed by the manufacture of components, assembly, Assembly quality control, packaging, and distribution of the completed product. The flowchart of the existing procedure exposes feasible vulnerable areas such as delays in the furnish chain, inefficiencies in the manufacture of aspect parts, and challenges with satisfactory control (Oliveira,2020).

The metrics needed to assess the process were developed and then measured. Cycle time, defect rate, inventory turnover, and overall customer satisfaction were some of the most important KPIs. According to the findings of the review, the existing procedure had a relatively high failure rate and longer cycle durations, both of which contributed to delivery delays of the product and decreased levels of customer satisfaction.

Techniques for the improvement of the process were implemented so that these flaws may be addressed. The concepts of Lean Six Sigma were used in order to cut down on cycle times and faults. The revised flowchart of the process includes modifications such as better techniques for quality control, optimal methods for inventory management, and simplified production procedures. It is expected that the implementation of these enhancements would end result in a discount in the range of defects, a shortening of cycle times, an enlarge in purchaser satisfaction, and an enlarge in the manufacturing process's basic efficiency.

It is projected, on the groundwork of the evaluation measures, that the future method will operate enormously higher than the existing condition. It is expected that the price of defects would go down, cycle times will be reducing down, and the degree of consumer delight will go up. Apple Company hopes that by means of inserting the advised modifications into action, it would be capable to enhance product quality, decrease delays, and make higher use of on hand resources (Sun,2021).

Collaboration amongst a large range of stakeholders, such as manufacturing teams, excellent manipulate specialists, and suppliers, is required for the manner enchantment mission that need to be executed in order to attain the future state. In order to warranty that the stronger method will proceed to be successful, we will be enforcing non-stop monitoring and information analysis, as properly as remarks loops (Gou,2019).

In summary, the analysis of Apple Company's production procedure unearthed several flaws in the process that are amenable to correction via the use of process improvement strategies. It is anticipated that the future process will perform better as a result of the implementation of the suggested enhancements, which would ultimately result in greater quality, decreased cycle times, and increased customer satisfaction.

References

Oliveira, N. N., Mothé, C. G., Mothé, M. G., & de Oliveira, L. G. (2020). Cashew nut and cashew apple: a scientific and technological monitoring worldwide review.  Journal of Food Science and Technology57, 12-21.

Sun, H., Xu, H., Liu, B., He, D., He, J., Zhang, H., & Geng, N. (2021). MEAN-SSD: A novel real-time detector for apple leaf diseases using improved light-weight convolutional neural networks.  Computers and Electronics in Agriculture189, 106379.

Gou, X., Zhang, W., Zhang, J., Zhang, J., & Zhang, J. (2019, October). Research on Simulation and Analysis of Monitoring Process of Hail-proof Apple Bagging Four-rotor Aircraft. In  IOP Conference Series: Materials Science and Engineering (Vol. 612, No. 5, p. 052030). IOP Publishing.