In a manufacturing company inventory cost is a significant part of expense. So, the Re-order Point (R.O.P.) of the items must be optimum to reduce its carrying cost. We have study about the inventory and R.O.P. in Nevatia Steel & Alloys Pvt. Ltd. Mumbai and tried to find the optimum R.O.P. by applying VED and XYZ Analysis. Finally, for mathematical modeling we also take help of MatLab

., Neetu

Bangar, Ajay

Sharma, Rajan

Tiwari, Vaibhav

English

Interscience Research Network

International Journal of Mechanical and Industrial Engineering Volume 2 Issue 1 Article 6 July 2012 Experimental Investigation & Evaluation of Incorporated Material to Set their Optimum Re-Order Point in Kanban Control Ajay Bangar Mechanical Engineering Department, Maharana Pratap College of Technology, Gwalior, Madhya Pradesh, India, abangar1000000@gmail.com Neetu . Mechanical Engineering Department, Maharana Pratap College of Technology, Gwalior, Madhya Pradesh, India., neetu04_311@rediffmail.com Rajan Sharma Maharana Pratap College of Technology, Gwalior, Madhya Pradesh, India, rjnsharma@rediffmail.com Vaibhav Tiwari Maharana Pratap College of Technology, Gwalior, Madhya Pradesh, India, vaibhavitmuniverse@gmail.com Follow this and additional works at: https://www.interscience.in/ijmie  Part of the Manufacturing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, and the Risk Analysis Commons Recommended Citation Bangar, Ajay; ., Neetu; Sharma, Rajan; and Tiwari, Vaibhav (2012) "Experimental Investigation & Evaluation of Incorporated Material to Set their Optimum Re-Order Point in Kanban Control," International Journal of Mechanical and Industrial Engineering: Vol. 2 : Iss. 1 , Article 6. DOI: 10.47893/IJMIE.2012.1061 Available at: https://www.interscience.in/ijmie/vol2/iss1/6 This Article is brought to you for free and open access by the Interscience Journals at Interscience Research Network. It has been accepted for inclusion in International Journal of Mechanical and Industrial Engineering by an authorized editor of Interscience Research Network. For more information, please contact sritampatnaik@gmail.com.     Experimental Investigation & Evaluation of Incorporated Material to Set their Optimum Re-Order Point in Kanban Control   Ajay Bangar, Neetu, Rajan Sharma, Vaibhav Tiwari Prof. Mechanical Engineering Department, Maharana Pratap College of Technology,                 Gwalior, Madhya Pradesh, India E-mail : abangar1000000@gmail.com, neetu04_311@rediffmail.com, rjnsharma@rediffmail.com, vaibhavitmuniverse@gmail.com   Abstract - In a manufacturing company inventory cost is a significant part of expense. So, the Re-order Point (R.O.P.) of the items must be optimum to reduce its carrying cost. We have study about the inventory and R.O.P. in Nevatia Steel & Alloys Pvt. Ltd. Mumbai and tried to find the optimum R.O.P. by applying VED and XYZ Analysis. Finally, for mathematical modeling we also take help of MatLab. Keywords - Re-order Point (R.O.P.), Inventory Carrying Cost (I.C.C.), VED analysis, XYZ analysis and MatLab R2008a.  I. INTRODUCTION  A. Literature History & Problem Identification:  In a manufacturing industry some items are vital from production point of view but inventory cost of these parts is very high. So, we cannot keep more safety stock for these kinds of items but unavailability of these items will stop the manufacturing operation of that plant. But now-a-days, business environment is highly uncertain which affects the lead time of the procurement of the items and we have to keep the safety stock of such items. It means that the company should achieve the balance between the safety stock they have to keep on hand and cost of carrying inventory. In this paper we tried to find out the optimum value of R.O.P. . II. DATA COLLECTION    TABLE I : DATA COLLECTED FROM NEVATIA STEEL & ALLOYS PVT. LTD. MUMBAI SR. No. Name of the Item Annual Requirement (S) Ordering Cost in Rs. (Cp) Unit Cost in Rs. (Cu) % of Average Inventory Investment (I) Lead Time (In Weeks) (LT) Consumption rate (CR)  Nature of the Item  Source of the supply   Way of the transportation Re-order Point (Weeks)(ROP) 1. a 80 980 570 1.8 1.6 1 Standard Local  Truck 36 2. b 1300 1.4 0.80 1.4 0.6 1130 Standard Local  Truck 42 3. c 940 1.3 0.70 1.6 1.1 645 Standard Local  Truck 42 4. d 2000 4 2.70 1.5 1.2 1730 Standard Local  Truck 42 5. e 4500 1.2 0.8 1.8 1.3 3678 Standard Local  Truck 42 6. f 1200 1.8 0.76 1.4 1.1 1015 Standard Local  Truck 42 7. g 1600 1.4 0.81 1.6 1.1 1340 Standard Local  Truck 42 8. h 800 360 257 2.3 1.3 560 Commercial  National Train 42 9. i 500 160 128 1.7 1.2 380 Commercial National Train 47 10. j 1200 360 185 1.6 3.0 1035 Standard Local  Truck 15 11. k 460 450 295 1.4 2.0 317 Commercial National  29 International Journal of Mechanical and Industrial Engineering (IJMIE), ISSN No. 2231 –6477, Volume-2, Issue-125 Experimental Investigation & Evaluation of Incorporated Material to Set their Optimum Re-Order Point in Kanban Control    SR. No. Name of the Item Annual Requirement (S) Ordering Cost in Rs. (Cp) Unit Cost in Rs. (Cu) % of Average Inventory Investment (I) Lead Time (In Weeks) (LT) Consumption rate (CR)  Nature of the Item  Source of the supply   Way of the transportation Re-order Point (Weeks)(ROP) 12. L 1800 1.2 0.7 1.5 1.5 1640 Commercial Local Truck 18 13. M 5 7800 6340 1.7 3.0 2 Commercial National Train 48 14. N 5 35000 32500 1.6 4.0 2 Buyers National Train 22 15. o 4 18000 16500 1.5 5.0 2 buyers national train 22 16. p 30 940 870 1.3 2.0 18  Standard National Train 18 17. q 1000 10 6 2.5 5.0 750 Standard National Train 60 18. r 3000 30 2 2 7.0 2830 Buyer’s design National Truck 35 19. s 60 4000 2875 1.6 3.0 27 Standard National Train 35 20. t 5000 40 5 5.0 6.0 3840 Buyer’s design Foreign  Ship  5 21. u 3000 48 8 2.3 3.0 2420 Buyer’s design National Truck 4 22. v 2400 280 180 1.4 4.0 2130 Buyer’s design National Truck 4 23. w 30 940 840 1.5 1.0 22 Standard Local  Truck 28 24. x 140 320 275 1.8 1.0 125 Commercial Local  Truck 28 25. y 1200 1.9 0.4 1.3 1.2 590 Standard Local  Truck 32  . III. METHODOLOGY  For this paper we have collected data from Nevatia Steel & Alloys Pvt. Ltd. Mumbai as shown in table I. On all the items we applied firstly VED Analysis and then XYZ Analysis. By applying both VED and XYZ Analysis we can find out such items which are very crucial and important from project point of view. So, methodology is applied on these five items. For finding  out the optimum R.O.P. we use the Regression Modelling with the help of MatLab software.  A. VED Analysis[7]  Here we ‘V’ is consider for ‘Vital’, ‘E’ is for ‘Essential’ and ‘D’ is for ‘Desirable’. The result of this analysis will be helpful in converging our focus on the ‘Vital items’, for which the level of inventory control required would be tighter than the parts.  For VED Analysis we consider following factors, which affects the R.O.P. of items in the industry: 1) Ordering cost(OC) (as per unit) 2) Lead Time (LT)(in Year) 3) Nature Of Item 4) Source Of Supply 5) Way Of Transportation    After finding out the factors which affects the R.O.P., we give them weightage according to their importance for R.O.P. For weightage of factors we draw a table as follows: []  TABLE II : FACTORS CONSIDERED FOR VED ANALYSIS WITH THE PLAN FOR WEIGHTAGE & POINT Sr. No. Factors First Degree Second Degree Third Degree 1. Ordering cost (5) OC<100 (5) 100≤OC≤1000 (10) OC>1000 (15) 2. Lead Time (20) LT <2 (20) 2≤ LT ≤4 (40) LT >4 (60) 3. Nature Of Item (20)  Buyer’s Design (20) Commercial (40) Standard (60) 4. Source Of Supply (25)  Local (25) National (50) Foreign (75) 5. Way Of Transportation (30) Truck (30) Train (60) Ship (90) International Journal of Mechanical and Industrial Engineering (IJMIE), ISSN No. 2231 –6477, Volume-2, Issue-126 Experimental Investigation & Evaluation of Incorporated Material to Set their Optimum Re-Order Point in Kanban Control    TABLE III : CATEGORIZATION OF V/E/D  On the basis of this table we categorized all the items into V or E or D as shown in Table IV.  Points Classification <150 Desirable (D) 150 to 175 Essential (E) >175 Vital (V) TABLE IV : CATEGORIZATION OF ITEMS INTO V/E/D Sr.  No. Name Of Item Ordering cost (A) Lead Time (B) Nature Of Item (C) Source Of Supply (D) Way Of Transportation (G) Total (A+B+C+D+G) Category (V/E/D) 1. a 10 20 60 25 30 145 D 2. b 5 20 60 25 30 140 D 3. c 5 20 60 25 30 140 D 4. d 5 20 60 25 30 140 D 5. e 5 20 60 25 30 140 D 6. f 5 20 60 25 30 140 D 7. g 5 20 60 25 30 140 D 8. h 10 20 40 50 60 180 V 9. i 10 20 40 50 60 180 V 10. j 10 40 60 25 30 165 E 11. k 10 40 40 25 30 145 D 12. l 5 20 40 25 30 120 D 13. m 15 40 40 50 30 175 E 14. n 15 40 20 50 60 185 V 15. o 15 60 20 50 60 205 V 16. p 10 40 60 50 60 220 V 17. q 5 60 60 50 60 235 V 18. r 5 60 20 50 30 165 E 19. s 15 40 60 50 60 225 V 20. t 5 60 20 75 90 250 V 21. u 5 40 20 50 30 145 D 22. v 10 40 20 50 30 150 E 23. w 10 20 60 25 30 145 D 24. x 10 20 40 25 30 125 D 25. y 5 20 60 25 30 135 D B. XYZ Analysis[7]  After VED Analysis we will switch over to XYZ Analysis. For this analysis we consider I.C.C. for categorization of items into X or Y or Z. Here we consider X for higher I.C.C., Y for medium I.C.C. and Z for lower I.C.C. as shown in Table V. The following formula of Economic Order Quantity (EOQ) and Inventory carrying Cost (I.C.C.) is used for all five items selected for XYZ Analysis.  EOQ = √ (2S * CP/ CU * I)  I.C.C. = (EOQ/2) * CU * I Here    S =  Annual requirements of items (nos.)     CP =  Ordering cost (as per unit)            CU = Manufacturing Cost or Unit Cost (Rs. Per   Unit)                    I = Inventory Investment  Factors considered for XYZ Analysis and Categorization  CATEGORIZATION OF ITEMS INTO X/Y/Z  Parameters Category X Y Z Inventory carrying Cost (I.C.C.) I.C.C.>200 200≥I.C.C.≥100 I.C.C.<100  COMBINED RESULTs OF VED & XYZ ANALYSIS Sr. No. Name of Item V/E/D Category (X/Y/Z) 1 a D X 2 b D Z 3 c D Z 4 d D Z 5 e D Z 6 f D Z 7 g D Z 8 h V X 9 i V X 10 j E X 11 k D X 12 l D Z 13 m E X 14 n V X 15 o V X 16 p V X 17 q V Z 18 r E Z 19 s V Z 20 t V Y 21 u D Y 22 v E X 23 w D X 24 x D X 25 y D Z International Journal of Mechanical and Industrial Engineering (IJMIE), ISSN No. 2231 –6477, Volume-2, Issue-127 Experimental Investigation & Evaluation of Incorporated Material to Set their Optimum Re-Order Point in Kanban Control    using this table we made a nine point matrix. In this matrix we distribute the entire items category into the combination of V/E/D and X/Y/Z. Nine point matrix X Y Z  h, i, n, o, p t q, s V j, m, v  r, E a, k, w, x u b, c, d, e, f, g, l, y D  By this table we find out five items h, i, n, o & p that comes into category of X and V. So, these five items are very crucial from project point of view. So, we applied methodology on these five items only.  C. Calculation for Re-Order Point (R.O.P.):  For calculation of R.O.P. we consider the following steps for all five items. For item h:  Annual consumption = 560 Items  EOQ = 312.16  Lead Time = 1.3 weeks =1.3/52= 0.025 Year  As 560 items consumed in 1 Year, so the 312.16 items will consume in 0.5581 Year but lead time of the item is 0.025 Year so the Re-Order of Item ‘h’ should be at least 0.025 Year before. So, appropriate Re-Order Point of Item ‘h’ is 0.5581-0.025=0.5331 Year. Same calculation is applied for items i, n, o & p then  For item i: ROP=0.6904 Year For item n: ROP= 12.8931 Year  For item o: ROP= 11.9638 Year For item p: ROP= 3.885 Year D. Modelling Of Parameters  To generalize the results, the Modelling of input parameters (Consumption Rate, Lead Time, ordering Cost, Inventory Investment & unit cost) and Re-Order Point (R.O.P.) is done using Regression Modelling and MatLab software R2008a. The parameters under consideration are 1) Consumption Rate (C.R.) 2) Ordering Cost (O.C.) 3) Lead Time (L.T.) 4) Inventory Investment (I.I.) 5) Unit Cost (U.C.) The Re-Order Point is a function of C.R., L.T., O.C., I.I. & U.C. So, we can take R.O.P. as: ln (R.P.) = C1 ln (C.R.) + C2 ln (O.C.) + C3 ln (L.T.) + C4 ln (I.I.) + C5 ln (U.C.)  Where, C1, C2, C3, C4, C5 are constants which are to be determined by Regression Modelling and using MATLAB software.   The output parameter Re-Order Point and input parameters are converted from actual absolute values to natural logarithms. For regression analysis, the natural logarithms of Re-Order Point is taken as single output parameter [Y] whereas natural logarithms of C.R. =[X1], L.T. =[X2], O.C. =[X3], I.I. =[X4] & U.C. =[X5] has been taken as input parameters X=[X1 X2 X3 X4 X5].  The following steps were followed and MATLAB is used. 1) Consider the output parameter natural logarithms of Re-Order Point (R.P.) [Y] and input parameters [X]. 2) X' = Transpose of [X] was determined. 3) X' Transpose of [X] was multiplied with [X] to get the product [X'*X]. 4) The inverse of product [X'*X] = [X'*X]-1 was obtained. 5) X' Transpose of [X] was multiplied with Re-Order Point (R.P.) [Y] to get the product = [X'*Y]. 6) Step 4 [X'*X]-1 was multiplied with step 5 [X'*Y] to obtain the product of [X'*X]-1 and [X'*Y]. 7) The final matrices found in the form of;     β 1   β 2 β  =  β3   Β4   Β5          Finally, after the completion of program and the values of constants found as follows:  • C1 = β1 • C2 = β2     • C3 = β3 • C4 = β4 • C5 = β5 International Journal of Mechanical and Industrial Engineering (IJMIE), ISSN No. 2231 –6477, Volume-2, Issue-128 Experimental Investigation & Evaluation of Incorporated Material to Set their Optimum Re-Order Point in Kanban Control    Stepwise MATLAB calculation is as follows:  Fig.1: Regression Modelling by using MATLAB R2008a  Fig. 2: Regression Modelling by using MATLAB R2008a  Fig. 3: Regression Modelling by using MATLAB R2008a From Regression Modelling we find out the values of ‘β’ shown as follows:   - 0.5749      0.6508 Β  = - 0.2929   - 0.3682   - 0.5899       From this result we get   β1 = - 0.5749    β1 =   0.6508    β1 = - 0.2929     β1 = - 0.3682     β1 = - 0.5899     The values of constants obtained are:     C1 = β1 = - 0.5749    C2 = β1 =   0.6508    C3 = β1 = - 0.2929    C4 = β1 = - 0.3682    C5 = β1 = - 0.5899       Substituting these values the equation of R.O.P.  becomes,   R.O.P. = (C.R.) ─0.5749 * (O.C.) 0.6508 * ((L.T.) -0.2929 * (I.I.) ─0.3682 * (U.C.) ─0.5899 IV. CONCLUSION  Inventory carrying cost is a vital part of economic analysis. It varies with no. of items and it’s Re-order Point (R.O.P.). By mathematical modelling we find out that R.O.P. of every item is directly proportional to its Ordering Cost and inversely proportional to its Consumption Rate, Lead Time, Inventory Investment and Unit Cost. The formula obtained for R.O.P. is  R.O.P. = (C.R.) ─0.5749 * (O.C.) 0.6508 * ((L.T.) -0.2929 * (I.I.) ─0.3682 * (U.C.) ─0.5899 V. ACKNOWLEDGEMENT  We gratefully acknowledge the inspiration provided by Professor V. M. Sahai, (Principal), Professor G.S.Tomar (Advisor), Professor Sanjay Goyal, and Professor A.K. Saxena, Professor Ashish Sastri of M.P.C.T.Gwalior to complete this research.   At last but not least we are very thankful to God who has blessed us to accomplish this work. International Journal of Mechanical and Industrial Engineering (IJMIE), ISSN No. 2231 –6477, Volume-2, Issue-129 Experimental Investigation & Evaluation of Incorporated Material to Set their Optimum Re-Order Point in Kanban Control    REFERENCES [ 1]. B. Chase Richard, “Production and Operation Mgmt.”, Eighth Edition, Tata Mc-Graw Hill, Page 431-433, 1999. [ 2]. Norman Gaither, “Production and Operation Management”, Sixth Edition, Page587, 1994. [ 3]. Martand Telsang, “Industrial Engineering and Production Management”, Second Edition, 2004. [ 4]. J.R. Tony Arnold & Lioyed M. Clive, “Introduction to Material Management”, McGraw Hill. [ 5]. Colin Drury, “Management and Cost Accounting”, Chapman& Hall. [ 6]. E. Thomas Vollmann & L.  William Berry, “Manufacturing Planning & Control System for Supply Chain Management”, McGraw Hill. [ 7]. Ross & Taylor, “Operations Management”, McGraw Hill. [ 8]. D. Chandra Bose, “Inventory Management”, McGraw Hill. [ 9]. N.K. Tiwari & K. Shishir Shandilya, “Ooperation Research”, McGraw Hill. [ 10]. D. Chandra Bose & Sandilya, “Fundamentals of Financial Management”, McGraw Hill. [ 11]. P. Gopalakrishnan & M. Sundaresan , “Materials Management an Integrated Approach”, McGraw Hill.    International Journal of Mechanical and Industrial Engineering (IJMIE), ISSN No. 2231 –6477, Volume-2, Issue-130

Experimental Investigation & Evaluation of Incorporated Material to Set their Optimum Re-Order Point in Kanban Control

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Experimental Investigation & Evaluation of Incorporated Material to Set their Optimum Re-Order Point in Kanban Control

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