Assessment Task
You will conduct a review of the academic literature on the subject of statistical process control.
Following your review, you are to analyse a given set of data to evaluate the performance of a fictional brewery in a given scenario.
You will be expected to illustrate your discussion with examples from academic journals, the trade press and other authoritative sources.
The word count should be 2000 words ±10% (tables, diagrams and appendices are excluded from the count).
Assessment Breakdown
1. Prepare a literature review on the subject of Statistical Process Control, covering the concept from its inception up to the present day.
Ensure that you include references to at least 10 peer-reviewed articles, no more than ten years old. You may also acknowledge older works, providing they are of sufficient importance in charting the development of SPC.
(50% of word count)
2. The supplied spreadsheet contains historic data recording the temperature of combined effluent discharged by a fictional brewery, Waterside Lager Limited (WLL). The data comprises temperatures recorded four times a day over the month of September 2022.
The brewery’s discharges are normally controlled within the range 25oC to 35oC. The maximum legally permitted temperature is 40oC.
Regular maintenance is performed on the balancing system (which neutralises the pH of the effluent at the expense of heating the discharge in the process), normally on a weekly basis.
Use the data to visualise the performance of the effluent control process, describing your analytical approach in detail. Include any graphs generated.
In your view, how well has the plant performed?
What priorities for quality improvements should the plant management set?
(50% of word count)Sheet1
27.508
33.19
30.0649
30.0102
27.6475
32.4864
24.1237
26.5117
33.9747
25.8427
31.5985
27.9439
34.7521
31.0639
33.2517
31.5985
32.8441
25.2503
26.3891
24.5012
27.9969
29.4594
28.2322
31.756
23.7669
27.6435
23.0705
24.8471
23.7561
25.3579
34.3809
27.1621
27.8763
26.8852
24.9195
32.045
33.6692
27.508
23.7561
34.3809
24.4551
30.8515
29.792
36.7611
31.2412
26.8945
36.4552
33.5425
36.5443
31.8286
32.9976
29.8895
30.5261
38.2822
32.4421
36.1361
32.6263
35.158
40.73
38.294
43.2163
43.8389
40.5347
38.1259
45.2167
36.6261
44.9231
39.5582
40.6913
39.8205
38.4995
40.2643
32.3862
40.14
36.1144
36.5583
37.1615
41.1681
33.9659
31.4491
29.0525
33.2361
28.9381
28.3651
33.5726
30.9505
34.6799
36.5684
34.7634
28.6535
31.4899
35.5593
34.4278
28.3744
30.2776
26.8801
33.4373
23.7654
22.4613
31.0189
30.7144
27.0994
26.3009
27.9834
20.6646
23.5196
26.6281
19.8736
24.9148
26.8165
28.8493
24.6247
25.5761
25.0189
19.1047
22.5525
18.8148
19.7404
16.2033
24.6646
Sheet2Assessment Brief
Module Code
Module Name
Managing Operations and the Supply Chain
Level
7
Module Leader
Andrew Gough
Module Code
BSOM046
Assessment title:
AS2: Statistical Process Control
Weighting:
60%
Submission dates:
13 January 2023
Feedback and Grades due:
12 February 2023
Please read the whole assessment brief before starting work on the Assessment Task.
Assessment Task
You will conduct a review of the academic literature on the subject of statistical process control.
Following your review, you are to analyse a given set of data to evaluate the performance of a
fictional brewery in a given scenario.
You will be expected to illustrate your discussion with examples from academic journals, the trade press and other authoritative sources.
The word count should be 2000 words ±10% (
tables, diagrams and appendices are excluded from the count).
Assessment Breakdown
1. Prepare a
literature review on the subject of
Statistical Process Control, covering the
concept from its
inception up to the
present day.
Ensure that you include references to at least
10 peer-reviewed articles, no more than ten years old. You may also acknowledge older works, providing they are of sufficient importance in
charting the development of SPC.
(50% of word count)
2. The supplied spreadsheet contains
historic data recording the
temperature of c
ombined effluent discharged by a fictional brewery, Waterside Lager Limited (WLL). The data comprises temperatures recorded
four times a day over the month of September 2022.
The brewery’s discharges are normally controlled within the range
25oC to 35oC. The maximum legally permitted temperature is
40oC.
Regular maintenance is performed on the balancing system (which neutralises the
pH of the effluent at the expense of
heating the
discharge in the process), normally on a weekly basis.
Use the data to
visualise the performance of the
effluent control process, describing your
analytical approach in detail. Include
any graphs generated.
In your view, how
well has the plant performed?
What
priorities for quality improvements should the plant management set?
(50% of word count)
Learning Outcomes
On successful completion of this assessment, you will be able to:
c) Critically discuss the managerial relevance of topics in business operations and supply management, analysing their benefits and implementation challenges to organisations and their supply chains.
d) Apply managerial concepts, theoretical frameworks and approaches to solve specModule Code: BSOM046
Assignment: ES1 – Statistical Process Control
Local Module Tutor: Mr. Melvin Goh
STATISTICAL
PROCESS
CONTROL
By: XXXXXX
Student ID: XXXXXXXX
FACULTY OF BUSINESS & LAW // MBA
Contents
1. Introduction ………………………………………………………………………………………………….. 1
2. Literature review …………………………………………………………………………………………… 1
2.1. Control charts for data types………………………………………………………………………. 2
2.2. Process capability …………………………………………………………………………………….. 5
3. Statistical analysis of Waterside Leather Limited ……………………………………………. 6
3.1. Capability test ………………………………………………………………………………………….. 8
4. Recommendations ………………………………………………………………………………………… 9
5. Conclusion …………………………………………………………………………………………………. 10
References ……………………………………………………………………………………………………….. 12
Appendix A: WLL’s historic data with control limits and moving range average …… 14
Appendix B: WLL’s historic temperature recordings (X-bar Chart) ………………………. 18
Appendix C: WLL’s process capability results ……………………………………………………. 19
1
1. Introduction
All organisations, whichever nature, compete on quality, delivery and price—all of which
requiring processes to facilitate the transformation of inputs into outputs in the form of
products, information, and services (Oakland and Oakland, 2019). Every task that’s to be
carried out within an organisation involves processes. While some are easily identified (e.g.
filling bottles with soda), others are less conspicuous (e.g. a personal assistant preparing a
report for her boss).
To be successful in today’s climate, organisations will need to commit to continuous
improvement and to be equipped with know-how in proper process management to ensure
quality. But operators and managers often mistook quality management as post-production
detection when it is essentially about managing quality at the point of production or
manufacture. To prevent customer dissatisfaction and to reduce waste incurred from poor
quality and the manufacturing of defective products, cost-effective quality control measures
must therefore be incorporated into processes. And to do so, it is highly recommended to
incorporate Statistical Process Control (SPC) which—succinctly defined—is to help
organisations achieve total quality management through process control andStatistical Process Control 1
STATISTICAL PROCESS CONTROL
by XXXXXXXX
Student ID: 2XXXXXXX
University of Northampton
(Amity Global Institute Pte Ltd, Singapore)
Managing Operations and The Supply Chain
Dr. Melvin Goh
BSOM046
BSOM046-SUM-1920-ES1-Statistical Process Control
18 Oct XXXX
Word Count: 1600 (± 50)
Statistical Process Control 2
Table of Content
1. Introduction………………………………………………………………….3
2. Literature Review……………………………………………………………3
3. Methodology…………………………………………………………………5
4. Case Study Analysis…………………………………………………………9
5. Recommendation…………………………………………………………….15
6. Conclusion……………………………………………………………………17
7. References……………………………………………………………………18
8. Appendix……………………………………………………………………..22
Statistical Process Control 3
STATISTICAL PROCESS CONTROL
INTRODUCTION
This report will provide a literature review of the concept and relevance of statistical process
control (SPC) from its inception until the present day. A case study of Waterside’s Leather
Limited (WLL) using the temperature data of its combined effluent discharge over one hundred
and twenty days will be conducted, and a recommendation will also be proposed.
LITERATURE REVIEW
Man has always tried to imitate and better his competitors to develop a better and cheaper
product or service. This idea was as crucial for the hunter-gatherer as it is for the manufacturing
industry after many millennia. This awareness led to the requirement of apprentices having to
follow in the footsteps of the master craftsmen for many years until they could become masters
in their craft. However, this was not a scientifically tabulated and monitored process.
Bradford and Miranti (2019) state that “it was in 1924 that Walter A. Shewhart introduced the
use of control charts to evaluate data distribution patterns to determine whether manufacturing
processes remain under control at Bell Telephone Laboratories”. He also introduced the terms
of variation in the process which comprises of common cause and special cause variation
(Subhabrata and Marien, 2019).
SPC is a technique for controlling processes to distinguish causes of variation and signal for
corrective action (Chen 2005 cited in Avakh and Nasari 2016). While some say that “SPC is
the use of statistically based tools and techniques principally for the management and
Statistical Process Control 4
improvement of processes” (Stapenhurrst, 2005), others say that “SPC is not really about
statistics or control, it is about competitiveness” (Oakland and Oakland, 2018).
Figure 1: A typical Control Chart
(Graph from https://learning.oreilly.com/library/view/nonparametric-statistical-process/9781118456033/c02.xhtml#head-2-
18)
The USA War Department used these methods to enhance the quality of products during World
War II. W.E Deming used Shewhart’s cycle in his quality training in Japan in 1950 but made
a new ve
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