This document presents a methodology for leveling low volume, high mix production using group technology principles. It involves clustering similar products into families, analyzing the families using ABC/XYZ, sequencing the families to minimize changeover time, calculating equipment utilization, and determining capacity slots in the production leveling pattern. The goal is to produce goods at a constant rate to reduce waste and unpredictability while accounting for differences in family volumes and demand variations.

1. Levelling Of Low Volume And High Mix Production Based On
A Group Technology Approach
Dinesh Chandra Pant
M.Tech- CAD,CAM & ROBOTICS
Indian Institute of Technology
Roorkee

2. WHAT IS PRODUCT LEVELLING?

3. PRODUCTION LEVELLING WITH AN EXAMPLE

4. PRODUCTION LEVELLING,
Also known as production smoothing or – by its Japanese original term –
heijunka, is a technique for reducing the mura (unevenness) which in turn
reduces muda (waste).
• It was vital to the development of production efficiency in the Toyota
production and lean production system.
• The goal is to produce intermediate goods at a constant rate so that further
processing may also be carried out at a constant and predictable rate.

5. THE NEED FOR HEIJUNKA
Large batches of the same product may reduce set-up times and changeovers,
but usually result in:
• Long lead times.
• Swelling inventories.
• Greater opportunities for defect.
• Excessive idle time and/or overtime.

6. Levelling of low
volume and high
Production mix
Product family
formation for
levelling
Levelling pattern
creation
•Selection of adequate grouping
criteria.
•Application of NSGA-II to optimize
attribute weights.
•Using k-means for clustering.
•Selection of a Pareto optimal
solution.
•ABC/XYZ analysis.
•Determination of a family sequence
with minimal changeover time.
•EFEI-Calculation.
•Determination of capacity slots in the
levelling pattern.
•Pattern improvement.
FLOW CHART FOR PRODUCTION LEVELLING

7. CLUSTER VALIDATION
Criteria for cluster validation-
• The first criterion is the homogeneity of the formed
families.
• The partition size.
• The size of the formed product families.
• the number of very small product families

8. DESIRABILITY INDEX
Desirability W is defined as :
W:{w1,w2.....wd} [0,1]
the desirability index W is defined as the geometric mean of four desirability:
𝑊 𝐶 𝐾 =
4
𝑖=1
4
𝑤𝑖
Where C(k) is the partition size of the family
𝑊1 𝐶
𝑘
= 1 − 𝑖=1
𝑘 𝑋 𝑗
𝑋𝑙
∈
𝐶 𝑘
,𝑗≠𝑙 𝑑(𝑋𝑗,𝑋𝑙)
𝑘 𝐶 𝑘
−1 2

9. 𝑊2 𝐶
𝑘
=
0 𝑘 = 1
𝑘 − 1
𝑘 𝑚𝑖𝑛 − 2
2
𝑘 ∈ {2,3 … . 𝑘 𝑚𝑖𝑛 − 1
1 𝑘 ∈ {𝑘 𝑚𝑖𝑛, 𝑘 𝑚𝑖𝑛 + 1 … .
𝑘 𝑚𝑎𝑥}
100 − 𝑘
100 − 𝑘 + 1
3
∈ {𝑘 𝑚𝑎𝑥 … . . 99}
0 𝑘 ∈ 𝑛 ∶ 𝑘 > 99
W3 𝐶
𝑘
= 1 −
𝑛 𝑤−𝑚𝑖𝑛𝐶
𝑘
𝑛𝑤)
maxC
𝑘
(𝑛𝑤)−𝑚𝑖𝑛𝐶
𝑘
𝑛 𝑤
𝑊4 𝐶
𝑘
= 2
− 𝛼

11. Identification of runner and stranger families
• Creation of the levelling pattern starts with family-based ABC/XYZ analysis.
• Families are segmented according to overall volume share and variation in
volume as well.
• Product families are divided into runner and stranger families.
• Runner families are characterized by high volume, high order frequency,
and low variation in demand.
• In contrast, strangers are produced in relatively low volume, low order
frequency, and high variation in demand.
LEVELLING PATTERN CREATION

12. ABC/XYZ ANALYSIS

13. SEQUENCING
The sequence of the families within the levelling cycle Significantly determines the
overall Change-over time that is Required to pass one cycle.
Travelling salesman Problem-
• The travelling salesman problem consists of a salesman and a set of cities.
• The salesman has to visit each one of the cities starting from a certain one (e.g.
The hometown) and returning to the same city.
• The challenge of the problem is that the travelling salesman wants to minimize
the total length of the path

14. 12
5
2
8
4 3
10
3
EXAMPLE OF TSP
The problem lies in finding a minimal path passing from all vertices once. For example the path Path1 {A,
B, C, D, E, A} and the path Path2 {A, B, C, E, D, A} pass all the vertices but Path1 has a total length of 24
and Path2 has a total length of 31.

15. EFEI CALCULATION
The available overall capacity for changeover of levelling families RLg(measured
in hours per month) is defined as:
RLg=[NGK*(1-KE)]-KRG
Where,
NGK represents the available net capacity,
KRG is the capacity required for production of levelling families (both measured
in hours per month) .
KE specifies the ratio of capacity required for production and changeover of
stranger families.

16. Calculation for available overall capacity of changeover

17. To determine the EFEI-value, the rounded off quotient lcth of overall capacity for
changeover of levelling families RLg changeover time required for one levelling
cycle RZ is used:
𝑙𝑐𝑡ℎ = |
𝑅𝐿𝑔
𝑅𝑍
|
𝐸𝐹𝐸𝐼𝑡ℎ =
𝐴𝑆
𝑙𝑐𝑡ℎ
Where AS represents the total quantity of working shifts per month
EFEI CALCULATION

18. DETERMINATION OF CAPACITY SLOTS
The chosen EFEI-value (EFEIch) determines the number of levelling cycles per month
lch
𝑙 𝑐ℎ =
𝐴𝑆
𝐸𝐹𝐸𝐼 𝑐ℎ
Based on this, capacity slots in the levelling pattern are determined for each levelling
family.
Such a capacity slot ZFi consists of a production and a changeover time component
𝑍𝐹𝑖 =
𝐾𝑅𝑖
𝑙𝑐 𝑐ℎ
+ 𝑟, 𝑖. . 𝑖 + 1

19. CONCLUSION
• This paper presents a systematic procedure for levelling low volume and
high mix production based on the principles of Group Technology.
• This procedure uses clustering techniques to subsume the large number of
product types into a manageable number of product families.
• These families are utilized to create a family-oriented levelling pattern.