You will conduct a review of the academic literature on the subject
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 |
Sheet2
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Assessment 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 specific operations and supply chain problems in a range of business case scenarios, including related implementation challenges. |
|
f) Produce and justify appropriate informed decisions in the context by elaborating pros and cons arguments concerning application of relevant concepts and managerial frameworks. |
Your grade will depend on how well you meet these learning outcomes in the way relevant for this assessment. Please see the final page of this document for further details of the criteria against which you will be assessed.
Assessment Support
Specific support sessions for this assessment will be provided by the module team and notified through NILE. You can also access individual support and guidance for your assessments from Library and Learning Services. Visit the Skills Hub to access this support and to discover the online support also available for assessments and academic skills.
Academic Integrity and Misconduct
Unless this is a group assessment, the work you produce must be your own, with work taken from any other source properly referenced and attributed. This means that it is an infringement of academic integrity and, therefore, academic misconduct to ask someone else to carry out all or some of the work for you, whether paid or unpaid, or to use the work of another student whether current or previously submitted.
For further guidance on what constitutes plagiarism, contract cheating or collusion, or any other infringement of academic integrity, please read the University’s Academic Integrity and Misconduct Policy. Other useful resources to help with understanding academic integrity are available from UNPAC – the University of Northampton’s Plagiarism Avoidance Course.
N.B. The penalties for academic misconduct are severe and include failing the assessment, failing the module and even expulsion from the university.
Assessment Submission
Written work submitted to TURNITIN will be subject to anti-plagiarism detection software. Turnitin checks student work for possible textual matches against internet available resources and its own proprietary database.
When you upload your work correctly to TURNITIN you will receive a receipt which is your record and proof of submission. If your assessment is not submitted to TURNITIN, rather than a receipt, you will see a green banner at the top of the screen that denotes successful submission.
N.B Work emailed directly to your tutor will not be marked.
Late submission of work
For first sits, if an item of assessment is submitted late and an extension has not been granted, the following will apply:
· Within one week of the original deadline – work will be marked and returned with full feedback and awarded a maximum bare pass grade.
· More than one week from original deadline – grade achievable LG (L indicating late).
For resits there are no allowances for work submitted late and it will be treated as a non-submission.
Please see the Assessment and Feedback Policy for full information on the processes related to assessment, grading and feedback, including anonymous grading. You will also find Guidance on grades and resit opportunities from the main University website. Also explained there are the meanings of the various G grades at the bottom of the grading scale including LG mentioned above.
Extensions
The University of Northampton’s general policy about extensions is to be supportive of students who have genuine difficulties in meeting an assessment deadline. It is not intended for use where pressures of work could have reasonably been anticipated.
For full details please refer to the Extensions Policy. Extensions are only available for first sits – they are not available for resits.
Mitigating Circumstances
For full guidance on Mitigating circumstances please go to Mitigating Circumstances where you will find information on the policy as well as guidance and the form for making an application. Please also see Extensions & Mitigating Circumstances guide 22_23 that compares your options.
Please note, however, that an application to defer an assessment on the grounds of mitigating circumstances should normally be made in advance of the submission deadline or examination date.
Feedback and Grades
These can be accessed through clicking on the “Gradebook” on NILE. Feedback will be provided by a rubric with summary comments.
3
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Module 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 and management.
2. Literature review
The objective of SPC lies in controlling and monitoring processes to help organisations
achieve competitive advantage. In order to manage processes effectively, it’s crucial to
understand that processes have variations, need proper control, have a capability and will
require improvements (Oakland and Oakland, 2019). It entails proper documentation of
procedures, includes the collection of reliable data about processes and data analysis, and
enables action to be taken to prevent failure or non-conformance with the desired
requirements—improving processes and leading to quality assurance as a result (Oakland
and Oakland, 2019). In essence, to continuously improve the quality of a process or product,
the role of SPC is to continuously reduce variations around a target (Ravichandran, 2017;
Abbas et al., 2018).
SPC however cannot operate independently. At its most fundamental level, it requires data
from sources the likes of operators, machines, and the Internet of Things (IoT), and must
harness the ability to present findings and notifications to the right stakeholders, at the
appropriate time and place so as to make effective, immediate decisions (Seland, 2019).
2
Therefore, to commission SPC, managers must identify the objectives they wish to achieve
before they can identify the right kind of parameters the SPC process will need.
2.1. Control charts for data types
Where it’s common to have variations in processes (e.g. common cause variations that are
considered inherent), SPC provides insights on whether processes are behaving as
specified and helps detect irregularities either through control by variables or control by
attributes through the use of control charts. Widely used to provide enhanced efficiency in
production, to reduce defects, improve profitability an
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