MSCI 342 Individual Coursework 2025
HindleTech Lift Modelling
Part A - Analysis of Historical Lift Data for HindleTech Tower [20 marks]
HindleTech own a commercial building in Manchester called HindleTech Tower, with 8 floors and a single lift. You will be supplied with a dataset of lift activity for a 14-day period in October 2024.
Day 1 is a Monday, day 2 is a Tuesday and so on.
Day 1:
1. How many lift trips were there?
2. Which floor experienced the most button presses?
3. Which floor was the most frequent destination floor for a trip?
4. What was the most common number of floors travelled (either up or down)?
5. Which hour of the day experienced the most trips (taken from when the button was pressed)?
The whole 14-day period:
6. What was the total number of trips?
7. Which day (1-14) experienced the most trips?
8. Which day of the week (1-7) experienced the most trips?
9. How many times did the lift visit floor 8?
10. What was the longest gap between button presses?
Part B - Flow Modelling of the HindleTech Tower Lift Activity [25 marks]
Develop a flow model for the lift activity in HindleTech Tower and use it to produce the following results. For all 14 days, the lift was free at 8:00am and positioned on floor 2.
Analysis of day 1:
11. What was the average waiting time for the lift?
12. What was the maximum waiting time for the lift?
13. How many trips involved no waiting at all?
14. How many trips involved a waiting time in excess of 1 minute?
15. What was the longest period of time when the lift was stationary?
The whole 14-day period:
16. Across all 14 days, how many times did the lift travel all 7 floors in a single trip (up or down)?
17. Across all 14 days, what was the total number of trips with no waiting?
18. Across all 14 days, what was the longest consecutive sequence of trips where the lift passenger had to wait?
19. Across all 14 days, how many floors did the lift travel in total, up and down?
20. Across all 14 days, how many floors did the lift travel in total, up and down?
Part C – Flow Modelling of the Isobel Mansions Lift Activity [15 marks]
Isobel Mansions is a residential building with 12 floors and two lifts.
You will be supplied with a dataset of lift activity for 5 days (Day 1 is a Monday).
Develop a flow model for the activity of the two lifts and use it to produce the following results.
Both lifts were free at 8:00am and positioned on floor 2.
Day 1 Analysis:
21. How many trips involved no waiting?
22. How many more trips did lift A undertake over lift B?
23. How many more floors did lift A travel over lift B, in total4?
24. What was the longest unbroken run of consecutive trips for a lift (lift A or lift B)?
25. What was the longest stationary period of time2 for a lift (lift A or lift B)?
Part D – Operational Changes to Isobel Mansions [15 marks]
The owners of Isobel Mansions are concerned with the lift performance and waiting times, and are considering installing new technology from the company ‘Superfast Lifts’.
Note: Each change is a separate, independent change.
26. SuperFast Lifts offer a new lift technology called MTFast™ whereby an empty lift can be operated at a faster speed compared to a lift with a passenger. They have provided a new travel time matrix for these empty lift movements. The lift speeds when a passenger is onboard would remain the same as currently.
What would be the impact on the number of trips waiting more than 10 seconds, if MTFast™ was adopted? Base your results on all 5 days of activity data. Write a brief conclusion to your analysis.
27. To perform. routine maintenance, the owners of Isobel Mansions are considering closing lift B for a day, and thus lift A would carry all the passengers that day.
What would be the impact on the number of trips waiting more than 10 seconds, if lift B was closed? Base your results on all 5 days of activity data. Write a brief conclusion to your analysis.
28. SuperFast Lifts also have a new technology called LiftDrop™ that will send an empty lift to a designated floor after a trip (if there isn’t already a lift at that floor, and there is sufficient time for it to get there before the next trip starts), rather than simply leaving the lift at the floor where it finished a trip. The lift sent would be the lift that gets to the designated floor the soonest.
If LiftDrop™ was implemented, and the designated floor is floor 1, what would be the impact on the number of trips waiting more than 10 seconds?
Base your results on all 5 days of activity data. Write a brief conclusion to your analysis.
Model Design [25 marks]
High marks will go to models which follows the design principles of the module, as laid out in the documentation and described during the lectures. The model should be well-designed, clearly laid out, easy to use and navigate, and with no unnecessary complexity. The model should also be flexible, transparent and be able to reproduce all the answers to the tasks should the data be altered or modified in the future.
Data
The data for each student is on moodle in a folder called ‘ HindleTech Data’.
Each student receives a unique dataset, based on a code number.
The code numbers are listed on moodle.
You MUST use the correct dataset, as all are unique. Failure to do so will result in inaccurate results.
Submission
You are required to upload to moodle a single Excel 2024 model addressing the tasks.
The model rules are:
The model should operate successfully and at a reasonable speed on a University-spec. PC
All answers should be provided in the correct cells on the User sheet
Any macros used to generate results must be included in the model
The model should not be password protected or contain links to external files
The model should not have any significant bugs or problems, such as circular references
No sheets should be hidden, and the sheet count should be reasonable
Failure to adopt these rules will result in a mark penalty
Deadline is 30th April 2025