This document summarizes a presentation about process control at Compaq. It discusses Compaq's build-to-order decision model and key performance measures like capacity, responsiveness, and inventory. It also covers process control strategies like push vs pull and build-to-order vs build-to-forecast. Specifics around Compaq's computer assembly line are provided, including station processing times and calculations of expected cycle times under different strategies using queueing theory models. The presentation concludes by discussing how optimal kanban sizes can be determined to minimize cycle times.

1. Process Control at Compaq®
Presented by –
• Debarpan Haldar (2207010)
• Dushyant Pratap (2207014)
• Rishabh Singh (2207025)
• Subhashish Das (2207026)
• Sumit Singh (2207027)
“Understanding the Build-to-Order Decision”

2. Compaq
launched ODM
(Optimised
Distribution
Model) to create
Customer Value
Revolution
Launching New Business Model
Compaq wants to be
here by implementing
JIT & KANBAN
Compaq is currently
here
Push Pull
BTO
BTF
WIP
FGI
Strategy

3. Process Performance Measures
3
Capacity
Responsiveness
Inventory
Measured by max. throughput rate
Measured by CRT

4. Inventories
Tactical
Inventories
Pipeline
Inventories
Finished goods
Inventory
Intermediate
Inventory
Raw Material
Inventory
WIP
Transportation
4

5. Time Measures
5
The time taken from the issuing of
a work order until the completion
of the order
The time a work order waits in the
order queue until it is “released”
to the (production) process
The time taken from the release of an
order into the (production) process
until the delivery of the finished
product (to the customer or to the FGI)
TPT = OQT + PCT

6. Inter-relation amongst process performance
measures
Increasing inventory will improve responsiveness, but also increase inventory carrying cost
Inventory incurs cost in the form of -
• Opportunity cost of financial capital
• The cost of product obsolescence
• Cost of maintaining warehouse operations
Increasing production capacity can reduce both inventory and response time at the cost of
increasing idleness
Compaq wishes to maximise the resource utilisation of its process, thus no need to increase the
capacity currently

7. Process Control Strategies
How much product needs to be
processed? (Process Loading)
Process loading decisions dictate when a
process work order is created
• Build-to-order (BTO)
• Build-to-forecast (BTF)
When exactly should the processing
be initiated? (Process release)
Process release decisions dictate when process
work orders are released into the process
• Push Strategy
• Pull Strategy

8. CRT = TPT = PCT
CRT ≤ TPT = PCT
CRT = TPT = OQT + PCT
CRT ≤ TPT = OQT + PCT

9. Serial Production Process of Computer Assembly
Install chip sets
Install PC
boards
Install power Install drives
If the processing time @ each station is 2 mins, then the stations capacity will be 30 computers/hrs

10. WIP Inventory Control
• Push (Unlimited WIP)
• Pull (WIP Inventory Control)
• Zero buffer
• Kanban square
• CONWIP
• Bottleneck starvation
avoidance Kan = Card
Ban = Signal
Kanban – trigger replenishment activity

11. MIN/MAX System: Visual Reorder Point
MAX
(Maximum Allowable)
MIN
(Minimum  Place
Order)
Safety Stock
Visual Signal
Positive signal
when depleted

12. Effect of
variability and
Kanban size
on Production
Capacity
(SD/µ)²

13. Mean Process Cycle Time (PCT) for Push and Pull WIP strategies
Little’s Law:
WIP =
Throughput*PCT

14. Comparison of BTO & BTF
BTO
• Process work orders are created only in response
to actual customer orders
• BTO strategy do not use FGI
• BTO/Pull strategies limit WIP inventories and
release process work orders only once WIP falls
below a certain level
• BTO-Push: CRT=TPT=PCT
• BTO-Pull: CRT=TPT=OQT+PCT
BTF
• Process work orders are created in anticipation of
customer demand
• BTF strategies use FGI to buffer the process from
demand
• BTF/Push strategies do not attempt to control WIP
inventories
• BTF-Push: CRT<=TPT=PCT
• BTF-Pull: CRT<=TPT=OQT+PCT

15. Given Data :
 CV²A = 1
 Mean Arrival rate (λ) = 23 computers/hour
 CV²S = 1
 τ = 2 minutes for each station
 Manufacturing Strategy – BTO/Pull

16. From Queueing theory,
Utilization rate = (23/30) = 0.77 ~ 77%, τi = Mean Service Time = 2 minutes
Wi = 2 x {0.77/(1-0.77)} = 26.5 minutes
E[CRT] = E[PCT] = ΣWi + τi = 26.5 + (2x4) = 34.5 minutes
E[CRT] is 34.5 minutes under the BTO push strategy.
Where(Wi) – expected time spent at each station

17. BTO/Push strategy

18. E[PCT] of the proposed BTO/Pull strategy with Kanban size

19. E[OQT] of the proposed BTO/Pull strategy with Kanban size

20. E[CRT] of the proposed BTO/Pull strategy with Kanban size

21. Conclusion
Initially, with increase in Kanban size PCT will decrease comparatively more than the increase
in OQT, thus overall CRT will reduce
After reaching optimal Kanban size, OQT will increase comparatively more than the decrease
in PCT with a further increase of Kanban size, which will result eventually increase CRT
In case of increased process variability (Cv=1) then increase in Kanban size would significantly
increase CRT
Compaq should trade-off between OQT and PCT by selecting optimal Kanban size (through
simulation) in BTO/Pull Strategy

22. Thank You!