Study of Process and Proposing a Transportation Model for Hand Woven Clothes from Weaving Mill : A Case Study

Study of Process and Proposing a Transportation Model for Hand Woven Clothes from Weaving Mill : A Case Study

Shyam Murali.C* ,

*ME Induusrial Engineering, PSG college of Technology, Coimbatore

A Prabhu karthi **

**Assistant Professor, PSG college of Technology,

Coimbatore

Abstract: In this article we describe and analyse the process flow and transportation optimisation of a weaving mill and distribution network. Cplex coding is done for proposing the transportation model. Use of control chart is plotting for the quality measure. It analyse the current distribution pattern and proposes a suggestion.

Keywords IBM Cplex, Control charts, Excel solver.

1. INTRODUCTION

   The goal of this article is to present a model of what are all the process happening in a weaving mill and their duration and scheduling, A transportation model is being proposed for the optimisation of total cost associated with it. Process flow is shown below, it is done with the help of MS Visio software. For transportation analysis IBM CPLEX coding can be use. This paper studies about all the process that is happening in weaving mill especially a hand weaving mill where all the process are semi-automated or say manual process are more than automated. The scope of automation in such industry will be very less compared to other weaving industry of same kind.

   Fig-1 Process Flow

2. PROCESS FLOW :

   a simple pictorial representation of the total flow the process associated with weaving from raw material entry to final product. This block layout is drawn using Microsoft visio. Raw material is pure cotton is undergone various processing stages that takes more than 2 weeks to get as a thread for weave. Cotton is undergone boiling process and converted to sliver (2 mm thick thread ) and then sliver to particular diameter thread. Colouring and strengthening is done by two subgroups as shown in picture. Machine setting time is crucial and time consuming activity, then weaving then QC. Quality rejected items are moves into scrap section that may reuse.

   Fig-2: Activity durations

   Activity duration is as above, here processing stage from raw cotton to thread takes large time duration compare to weaving time.

   For quality checking as per the flow process shown above, they are concerned with following

   There may be a chance of occurring following defects

   1. Thread braking

   2. No. of thread sets ( ooda ) are more or less 19 20 .

   3. Improper sides.

   4. Length variation

      In this article we measure the process capability by various metrices using Minitab and plotting the X bar R chart to see the variations.

      Table 1 length measured

      A sample consist of 5 units and such type of 20 samples taken for observation. Control charts (using X bar and R chart) using Minitab gives following results.

      Fig .2 Control chart ( Xbar and R )

      = 0.000101599

      ie 101 parts per million

3. DISTRIBUTION

   Under the Central weaving board there having mainly 3 weaving centre at

   1. Payyannur

   2. Munnad

   3. Periye

   Finished products from all these centres moves to central office stock room at Payyannur.

   There are 12 outlets in Kasaragod district, in that 4 are main.

   1.Kundamkuzhy 2.Kasaragod 3.Neeleswaram 4.Kanhangad

   Source capacity and destination demand details are a follows.

   A factor is being multiplied with the real value to comprehend with the company policy.

   Some assumptions we are taking as follows

   • Taken only main destinations

   • Lions share of the capacity consumes by these 4 outlets

   • Assume 60% of capacity

   Standard deviation = d2

   = 3.970

   2.326

   = 1.7067

   Total Cost = ( 390*78) + ( 390*64)

   = 55380 Rs

   Process Capability Ratio =

   USL – LSL =

   6

   190 – 185

   6 *1.17067

   =0.488

   implies natural tolerance limits in the process are not inside the 6 sigma limits.

   Total Cost = (73*300) + (87*400) + (30*300) + (41*350)

   = 80050 Rs

   Sigma level =

   USL – Mean =

   190 – 187.4

   1.7067

   = 1.52

   Ie the process follows 1.52 sigma level

   Fraction of non-conforming item P = P( x<185) + (x>190)

   = (185 – 187.4

   1.7067

   ) + ( 190 -187.4 )

   1.7067

   From the observation its clear that current practice they are doing holds more capital expense for transportation.

4. RESULT

   From the transportation results it is clear that it is spend much more capital expense in terms of transportation of finished goods. So here is the proposal for transportation leads overall profit in capital

5. CONCLUSION

With those assumptions we made earlier proposed transportation model will give an optimised result. Since the factor which we taken for comprehend the company policy we cannot tell exact or percentage of the savings that we can made. The result shows that the proposed model can save a reasonable amount of capital that the company may invest on it. The process is being studied and since it is a manual operations all over there is no scope of automation or any sort of improvement in that area. But there is a scope for improving in inventory and productivity improvement side by applying various lean tools in future.

REFERENCES

Fig.3 Transportation model Cplex Code

We makes a suggestion that a transportation arrangement by making Cost matrix. The fig.3 shows a Cplex code for transportation model with constraints as demand and supply.

Fig. 4 Cost matrix data

Here constrains are the demands of each outlets and capacity of each weaving centre. And the assignment for each outlet and centre found by using excel solver.

This will be the final basic feasible solution

Total Cost = ( 300*5) + (90*25) + (350*30) + (270*41) + (310*21) + (80*12)

= 30740 Rs

1. Gaurav Sharma, S. H. Abbas, Vijay Kumar Gupta, International Journal of Engineering And Science Vol.5, Issue 7 (July 2015), PP – 23-26, Solving Time Minimizing Transportation Problem by Zero Point Method.

2. P. Pandian and G. Natarajan, Applied Mathematical Sciences, Vol. 4, 2010, no. 37, 1819 1830 A New Method for Finding an Optimal Solution of Fully Interval Integer Transportation Problems

3. Sepideh Khalafi, Sadigh Raissi , IJSTR 3, ISSUE 6, JUNE 2014 Industrial Valves Production Line Bottleneck Analysis: A Computer Based Simulation Approach

4. Satish Verma, Dr. Sridhar. K, Ankit Kashyap (SSRG-IJME) volume

   2 Issue 5May 2015 GAME THEORY PROBLEMS BY AN ALTERNATIVE SIMPLEX

5. Mohammad Shyfur Rahman Chowdhury, Mohammad Toufiqur Rahman and Mohammad Rokibul Kabir, (Jun-2013), Linear Programming based Scenario Reduction using Transportation Distance (IOSR-JBM) Volume 10, Issue 1 (May. – Jun. 2013), PP 22- 29.