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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