- Demonstrate understanding of the principles and techniques associated with
simulation modelling, business process and logic modelling languages.
- Use simulation techniques and software to develop and evaluate appropriate
scenarios for using in the analysis and evaluation of business plan alternatives.
- Understand the concept of probability/randomness and how it can be modelled to
produce realistic simulation models.
- Develop a working knowledge of a discrete-event simulation software package
such as SIMUL8/ARENA.
A shop floor is the area in a manufacturing facility where production is carried out, by machines and
operators. In this scenario, a shop floor consists of 3 production sections, each section has 2 operations is
considered. These operations are repeated/similar across all sections, so that arrived jobs can be
processed at any section. Jobs frequently arrive at irregular/random intervals and can select any of the
sections based on the queue size (least).
The job shop manufacturing system encountered many scheduling problems. These problems include
variations in batch sizes, processing times, inventory levels, work in progress (WIP), performance, etc.
The following description shows the flow of operations in this shop floor.
• The inter-arrival times of jobs (in minutes) follow a user-defined distribution based on
Exponential with an Average equal to 10.
• The shop floor consists of 3 production sections (Section 1, Section 2, and Section 3). See Figure
1 for the shop floor layout.
Figure 1: schematic diagram of the shop floor
• Upon arrival, the job selects a production section based on the shortest queue size.
• Each section has two operations, these operations are repeated across all sections. See Table 1
for the shop floor operations.
Table 1: Shop floor operations
1 Operation 1 and 2
2 Operation 1 and 2
3 Operation 1 and 2
• Two machines are used at each section. These machines are similar across all sections. Although
these machines are similar, each production section has its own (not shared) machines. See Table
2 for further information about the used machines.
Table 2: Machines used in each section
1 M1-1 M2-1
2 M1-2 M2-2
3 M1-3 M2-3
- M1-1 refers to machine 1, section 1 location
• Four skilled operators are working in the shop floor, some of these operates can operate more
than one machine (multi-skills). Each machine requires only 1 operator allocated with the
related skill. See Table 3 for skills of operators.
Table 3: Skills of operators
- 1 Machine requires only 1 operator
• Each section has different efficiency in terms of operational/process time. This depends on the
allocated operator’s performance (represented here by random expressions). See Table 4 for
section/operation process times.
Table 4: Process times of each shop (in minutes)
OPERATION 1 OPERATION 2
1 UNIF( 10 , 20 ) 25
2 35 TRIA( 22 , 35 , 43 )
3 50 60
• Only one job can be processed at a time.
• The service discipline follows the First-In-First-Out rule.
Increasing productivity is the first industry priority and this leads to using sophisticated technologies that
have changed the outlook of the shop floor. One of these technologies is computer simulation that is used
to imitate the shop floor operations for best performance of resources including operators and machines.
For this piece of individual coursework, you are required to apply simulation modelling to
deliver the tasks below:
Task 1- After reading the scenario above, provide problem brief, main aim, objectives, tools and
techniques, and key performance indicators.
Task 2- Use tabular form to define and analyse the Shop Floor Scheduling problem. This analysis
includes decomposing the system being investigated into its main components including entities,
attributes, activities, state variables, and events.
Task 3- An appropriate flowchart with detailed explanations.
Task 4- An appropriate Activity Cycle Diagram (ACD) with detailed explanations.
Task 5- Develop a business simulation model for 200 jobs to imitate the above scheduling problem
(“As-Is” situation) in order to increase productivity of the shop floor operations. Five simulation runs are
required, at least two experiments (scenarios) to achieve a reasonable:
i. Overall simulation time.
ii. Queue size at each.
iii. Average waiting time.
iv. Resource(s)/ service facility(s) utilisations.
A comparison via Excel diagrams of the “As-Is” scenario with any other improvement scenarios “WhatIf” is required.
Task 6- Conclusion and Recommendations for further improvement (bullet points)
✓ The Hand-out Date: Monday, 5th October 2020
✓ Online Submission – by 18:00, Monday 30th November 2020 online submission via
Moodle/AULA. The mandatory submission components are:
o A detailed report including all the required tasks 1-6, system analysis table, flowchart
diagram, Activity Cycle Diagram (ACD), both ‘As-Is’ & ‘What-If’ simulation models/
snapshots & other relevant comparison diagrams (outlines are provided above).
o A copy of the developed “As-Is” simulation model (.s8 extension)
o A copy of each of the developed “What-If” scenario (.s8 extension)
o A copy of Excel file including all scenarios allocated in multiple sheet tables (‘As-Is’ &
‘What-If’) and their experiments outputs, analysis plus overall comparison diagrams.
✓ Report Word limitation: 1500 words as an individual report (for the body of the report,
excluding Bibliography, References, and Appendices
- You are expected to use the CUHarvard referencing format. For support and advice on how this
students can contact Centre for Academic Writing (CAW).
- Please notify your registry course support team and module leader for disability support.
- Any student requiring an extension or deferral should follow the university process as outlined
- The University cannot take responsibility for any coursework lost or corrupted on disks, laptops
or personal computer. Students should therefore regularly back-up any work and are advised to
save it on the University system.
- If there are technical or performance issues that prevent students submitting coursework through
the online coursework submission system on the day of a coursework deadline, an appropriate
extension to the coursework submission deadline will be agreed. This extension will normally be
24 hours or the next working day if the deadline falls on a Friday or over the weekend period.
This will be communicated via email and as a CUMoodle announcement.
- Students are reminded of the requirement to comply at all times with CU’s Academic Conduct
policy & procedures. Further details are available via the Student Portal on the CU website and
in the Student Handbook.
- Assessment Criteria
The following criteria will be interpreted appropriately according to the nature of the assessment and the
general framework set by the module aim and learning outcomes.
For a Bare Pass Mark (35%)
• Work lacks any academic merit as adjudged by the foregoing.
For an Excellent Mark (>69%)
• Show a thorough understanding of the purpose of the activity.
• Display knowledge of all the relevant principles, theories, and practices and an ability to apply
• Provide evidence of extensive reading beyond that listed, including academic journals.
• Demonstrate an ability to select critical points, evaluate them and communicate the conclusions
• Develop and run models that reflect as realistically and sensibly as possible given situations.
• Develop and run models that are based on sensible and useful options that go beyond given
• Provide analysis, discussion, and comment critically on the results produced by models.
• Provide solutions to business problems that are creative and practicable.
• Provide sound, supported, discussions of further research that may be needed.
Feedback and Support Method: Individual written feedback to be provided on Moodle/AULA:
A slot of time will be allocated to provide students with a brief on all the assignment elements. Students are
welcome to contact the lecturer during his contact hours/ THETA hours for any further assistance. However, there
is a clear marking scheme/ direction on the bottom of this coursework directing students on how to prepare and
manage their outputs for best achievement.