Get Instant Help From 5000+ Experts For

Writing: Get your essay and assignment written from scratch by PhD expert

Rewriting: Paraphrase or rewrite your friend's essay with similar meaning at reduced cost

1. Discuss and formulate the scenarios relevant for answering different questions
2. Demonstrate the interpretation of computer output to answer different questions

Analysis of Data

The use of information technology has affected the business process in all aspect. But use of information technology in Supply chain management, has totally chained the face of doing business, all the jargons like E-Commerce, EDI, ERP, Barcode, QR code, 3PL, all are only possible after the application of computer in supply chain management. Here we will see that how optimization can be done in limited resources with the help of computer application (Szpilko, 2017).

As given in the question, the first work to John smith is the analyses the data as given in question, the normal demand of Mech. wire is around 4276 unit, and average output is around 2400 unit/month, Therefore it clear that, we have to arrange all the resources to maximize the profit from the given output. The main difference in output and demand is due to the reason, that, the plant’s machine utilization is around 63%. By analysis and calculation we try to find, how we can optimize the available machine and resources in give condition. We will solve this problem with the help of excel solver in Microsoft Excel 2016 (Štefan Kudlá?, 2017).

The given situation, is suitable for linear programming, and this will be done by using excel solver, because, if we see the data we can analyze, LP is only the tools which can be used for this situation, The summary of data is as given below,

 1 Next Month Order Product Units ordered W0075C 1,400 W0033C 250 W0005X 1,510 W0007X 1,116
 2 Standard Cost Product Material Labour Overhead Selling Price W0075C \$33.00 \$9.90 \$23.10 \$100.00 W0033C \$25.00 \$7.50 \$17.50 \$80.00 W0005X \$35.00 \$10.50 \$24.50 \$130.00 W0007X \$75.00 \$11.25 \$64.75 \$175.00
 4 Plant Capacity Drawing Extrusion Winding Packaging 4,000 4,200 2,000 2,300

The above plant capacity data is full capacity data, but in question it is given that, the average machine utilization is 63% and 5% production is going to rework from winding, in this condition the utilized plant capacity is given as follows.

 6 Capacity utilised(Actual) 2,520 2,646 1,197 1,449

And finally the bill of labor is given as

 5 Bill of labour (hours/unit) Product Drawing Extrusion Winding Packaging W0075C 1 1 1 1 W0033C 2 1 3 0 W0005X 0 4 0 3 W0007X 1 1 0 2

From the above situation we will formulate the linear programming which is as follows,

The actual profit /unit of wire can be taken as

Actual profit = Sell Price – (Material + labor + overhead)

The profit calculated for four different products is as follows,

 W0075C W0033C W0005X W0007X \$34.00 \$30.00 \$60.00 \$25.00

Suppose, product W0075C is denoted as X1, similarly other product, W0033C, W0005X, W0007X is X2, X3, and X4 respectively, then our total profit will be calculated as

34x X1 + 30x X2 + 60x X3 + 25x X4 = Z, this will be objective which I have to maximize according to the above data.

The constraint can be given as

For plant capacity,

X1 + 2X2 + X4   2520 …………(i)

X1 + X2 + 4X3 + X4   2646 …..... (ii)

## Formulating the Linear Programming

X1 + 3X2   1197 ……………..…(iii)

X1 + 3X3 + 2X4  1449 …………..(iv)

For demand capacity

X1  1400 …………………..(v)

X2  250 ……………………(vi)

X3  1510…………….……..(vii)

X4  1116, ……………..(viii)

Two more constrains is there because of commitment done by Vivian Napoli.

X1  150 ………………(ix)

X4  600 ………………(x)

Now to calculate the maximum capacity from the given data, we have to run the excel solver and put all the data as given in excel sheet.

 Product W0075C W0033C W0005X W0007X Units 249 250 0 600 Profit/Unit \$34.00 \$30.00 \$60.00 \$25.00 \$30,966.00 Available constraints W0075C orders 1 0 0 0 249.00 <= 1400 W0033C orders 0 1 0 0 250.00 <= 250 W0005X orders 0 0 1 0 0.00 <= 1510 W0007X orders 0 0 0 1 600.00 <= 1116 Drawing time 1 2 0 1 1349.00 <= 2520 Extrusion time 1 1 4 1 1099.00 <= 2646 Winding time 1 3 0 0 999.00 <= 1197 Packaging time 1 0 3 2 1449.00 <= 1449 Minimum W0075C 1 0 0 0 249.00 >= 150 Minimum W0007X 0 0 0 1 600.00 >= 600

The cell given in green is calculated maximum profit for given condition. The answer report and sensitivity analysis is given in excel sheet.

If we will see the utilisation of different section we will observe that, the % utilisation of different section i.e. Drawing, Extrusion, Winding and Packaging, we see that, it is around 53%, 41%, 83% and 100% for packaging, in this condition, it is clear that, almost half of the manpower in drawing section and extrusion section is unused, If by any means If we shift the manpower to winding, and packaging section, we can increase the output,

Suppose by shifting the manpower, we have increased the rated capacity of winding and packaging, in this condition we must put the maximum value of winding and packaging.

After running the solver but putting the value 2000 and 2300 for winding and packaging, the result is as follows

 Product W0075C W0033C W0005X W0007X Units 1100 250 0 600 Profit/Unit \$34.00 \$30.00 \$60.00 \$25.00 \$59,900.00 Available constraints W0075C orders 1 0 0 0 1100.00 <= 1400 W0033C orders 0 1 0 0 250.00 <= 250 W0005X orders 0 0 1 0 0.00 <= 1510 W0007X orders 0 0 0 1 600.00 <= 1116 Drawing time 1 2 0 1 2200.00 <= 2520 Extrusion time 1 1 4 1 1950.00 <= 2646 Winding time 1 3 0 0 1850.00 <= 2000 Packaging time 1 0 3 2 2300.00 <= 2300 Minimum W0075C 1 0 0 0 1100.00 >= 150 Minimum W0007X 0 0 0 1 600.00 >= 600

From the above solution it is clear that, if we shift the worker bay any means from drawing and extrusion department, the profit can be increase in such a way that, we can fulfil the required condition and earn maximum profit as profit \$ 59,900.

The solution optimised solution suggest that, the product W0005X is not produced to maximise the profit, even profit margin for W0005X is highest, but it is also taking resources highest. The commitment done by Vivian Napoli can be easily fulfilled with the above condition,

Therefore, main problem is here is low utilisation of machine, and the mains constraints are packaging time, it is still clear from the above table is that if by any means we increase the packaging limit we can produce more with the given constraints, even if we increase the packaging by 3000, the almost all resources will be utilised and profit will be around \$ 77000,

The best recommendation for john smith is that, it should stop producing W0005X, because resources are greatly utilised and any how increase the capacity of packaging department, so that maximum profit can be done without any further investment. The other recommendation is that the number of rejection should be reduced to, because this 5% will directly add to the profit margin.

## Running Excel Solver

If we want to perform the sensitivity analysis for this problem, we have to develop table to identify the related information obtained from the sensitivity analysis, but sensitivity is not the report which can be presented directly to the meeting, we must change into lucrative form so that it can be presented.

The Sensitivity analysis of the above problem is given as follows,

 Microsoft Excel 14.0 Sensitivity Report Worksheet: [806856.xlsx]Sheet1 Report Created: 30-09-2018 04:08:42 Variable Cells Final Reduced Objective Allowable Allowable Cell Name Value Cost Coefficient Increase Decrease \$J\$4 Units W0075C 1100 0 34 1E+30 14 \$K\$4 Units W0033C 250 0 30 1E+30 30 \$L\$4 Units W0005X 0 -42 60 42 1E+30 \$M\$4 Units W0007X 600 0 25 43 1E+30 Constraints Final Shadow Constraint Allowable Allowable Cell Name Value Price R.H. Side Increase Decrease \$N\$10 W0075C orders 1100 0 1400 1E+30 300 \$N\$11 W0033C orders 250 30 250 50 250 \$N\$12 W0005X orders 0 0 1510 1E+30 1510 \$N\$13 W0007X orders 600 0 1116 1E+30 516 \$N\$14 Drawing time 2200 0 2520 1E+30 320 \$N\$15 Extrusion time 1950 0 2646 1E+30 696 \$N\$16 Winding time 1850 0 2000 1E+30 150 \$N\$17 Packaging time 2300 34 2300 150 950 \$N\$18 Minimum W0075C 1100 0 150 950 1E+30 \$N\$19 Minimum W0007X 600 -43 600 475 75

As per the report given above, we can analyses the situation; we can compare the production report with actual order report and can see that how much I have fulfilled the demand. In this way we can also show the way for management that which product is more necessary to produce.

 Product Units ordered Order Produced Difference W0075C 1,400 1100 300 W0033C 250 250 0 W0005X 1,510 0 1510 W0007X 1,116 600 516

The total product produce is 1950 against the order 4276, in this production; we have fulfilled the demand of product W0033C. Additionally I have fulfilled the demand of Vivian Napoli. The production of W0005X is not taken into consideration by solver, even it is the product of maximum margin, but in terms of resources, this product is grabbing too many resources, therefore for maximum profit, the product W0005X is stopped.

Further looking into the Sensitivity analysis we can see that, we have to put the actual order and find the differences the cost is gone up by \$42 and profit go by \$ 102, but removing it cost is decrease by \$42 and we get maximum profit after removing the W0005X.

Another aspect we can analyse is that, the utilisation of resources in each department.

 Department Given Cap. Resources consumed Unutilised Drawing 4000 2200 1800 Extrusion 4200 1950 2250 Winding 2000 1850 150 Packaging 2300 2300 0

From the above table we can see that, the as per capacity of plant, the resources unitised are almost 50% for drawing and extrusion, and resources for winding is around 95%, but resources for packaging is fully utilised. Therefore, packaging is the bottleneck for the operation, we must exploit and subordinate the packaging section, so that, further resources can be utilized. For fully utilising the other resources, we must increase the packaging resource up to 3000 hr.

The limit report is also providing the same thing

 Microsoft Excel 14.0 Limits Report Worksheet: [806856.xlsx]Sheet1 Report Created: 30-09-2018 04:08:42 Objective Cell Name Value \$N\$5 Profit/Unit ? 59,900.00 Variable Lower Objective Upper Objective Cell Name Value Limit Result Limit Result \$J\$4 Units W0075C 1100 150 27600 1100 59900 \$K\$4 Units W0033C 250 0 52400 250 59900 \$L\$4 Units W0005X 0 0 59900 0 59900 \$M\$4 Units W0007X 600 600 59900 600 59900

The binding of constraints can also be visible in this section

 Cell Name Cell Value Formula Status Slack \$N\$10 W0075C orders 1100.00 \$N\$10<=\$P\$10 Not Binding 300 \$N\$11 W0033C orders 250.00 \$N\$11<=\$P\$11 Binding 0 \$N\$12 W0005X orders 0.00 \$N\$12<=\$P\$12 Not Binding 1510 \$N\$13 W0007X orders 600.00 \$N\$13<=\$P\$13 Not Binding 516 \$N\$14 Drawing time 2200.00 \$N\$14<=\$P\$14 Not Binding 320 \$N\$15 Extrusion time 1950.00 \$N\$15<=\$P\$15 Not Binding 696 \$N\$16 Winding time 1850.00 \$N\$16<=\$P\$16 Not Binding 150 \$N\$17 Packaging time 2300.00 \$N\$17<=\$P\$17 Binding 0 \$N\$18 Minimum W0075C 1100.00 \$N\$18>=\$P\$18 Not Binding 950.00 \$N\$19 Minimum W0007X 600.00 \$N\$19>=\$P\$19 Binding 0.00

Here we can clearly see that the binding of data comes in W0033C order and packaging time. The order is as per demand, but packaging time is something which we can control.

As we have seen in the table and Sensitivity report above, it clear that, the drawing department is underutilized, in this condition we should not send the temporary labor to drawing department, rather we should send it to packaging department, In fact not need of temporary worker, here, we can utilize own worker of the company to manage the packaging department, One important information from the above reports is that, if we increase packaging hour by 1, out inherited profit will rise by \$34, this packaging hour can go up to, 2500 hour without any additional resources. But if we further want to increase the profitability, we have to add some winding hour also, this will give leverage to increase the profit.

## Sensitivity Analysis

Conclusion

The use of excel solver becomes very common for purpose of optimization problem. The main reason behind this is easy to use Solver tools given in Microsoft excel. The use of complex mathematical concept is history, when linear programming being solved by Simplex method or any other manual method, in 1950s when linear programing first used in US military, to find the low cost diet with highest nutrition value by Jerry Cornfield, it took 2 years to find the optimized value, but today with the use of computer we can dot in two hours or less.

This is the report which can be presented by John Smith to the management. There are various other possible permutation and combination of data by which we can analyses the result obtained from solver. If manpower is given for department, we can reschedule the entire problem in better optimization using this solver.

Ahmed Ghaithan, A, A, S, D, 2017, Multi-objective optimization model for a downstream oil and gas supply chain, King Fahd University of Petroleum & Minerals, 1(1), pp, 1-20.

Anon, 2016, Lean Six Sigma Applications in Oil and Gas Industry: Case Studies, The Petroleum Institute, 1(1), pp, 1-5.

Barker, J, A, 2014, From the Depths of Despair to the Promise of Presence, 1st ed, New York: Eisenbrauns.

Ba-Shammakh, M, 2009, An Optimization Approach for Integrating Planning and CO2 Mitigation in the Power and Refinery Sectors, University of Waterloo, pp, 1-202.

Choudhary, A, 2014, ANALYSIS AND DESIGN OF SUPPLY CHAIN MODEL FOR A SPECIFIC ORGANISATION, The Macrotheme Review, pp, 1-36.

Jaber, D, S, A, A, 2015, ADNOC group sustainability report, Adnoc journal, pp, 1-11.

Jianhua Dai, S, P, S, L, 2017, Mitigation of Bullwhip Effect in Supply Chain Inventory Management Model, Manufacturing and Management, 1(1), pp, 1-6.

Joseph Geunes, P, P, 2009, Supply chian optimisation, Applied Optimization techniques, 98(1), pp, 1-418.

ling, R, 2017, Investment guide to UAE, Framework for investments journal, 1(1), pp, 1-48.

Mahmood, Y, H, 2015, Capacity consraints management stretegies and supply chian performance of petroleum industries, Business adminitration school journal, 1(1), pp, 1-81.

Michael Talmadge, L, B, P, L, 2016, Optimizing Biorefinery Design and Operations via Linear Programming Models, Symposium on Thermal and Catalytic Sciences, pp, 1-1.

O’Leary, 2014, Introduction to literature review, Literature review, 1(1), pp, 1-9.

Panos Pardalos, D,-Z, D, 2009, Optimisation and logistic challenges in the enterprize, Springer Optimization and Its Applications, 1(1), pp, 1-430.

Raed Hussaian, B, K, 2006, Supply Chain Management in the PetroleumIndustry: Challenges and Opportunities, International Journal of Global Logistics & Supply Chain Management, 1(2), pp, 90-97.

Sharada Vadali, S, C, 2016, Buyer-Supplier Transport Access Measures for Industry Clusters, Texas A&M University System, 1(1), pp, 1-11.

Cite This Work

"Optimization Of Production Through Linear Programming: An Essay.." My Assignment Help, 2021, https://myassignmenthelp.com/free-samples/ops910-supply-chain-analytics/additional-resources.html.

My Assignment Help (2021) Optimization Of Production Through Linear Programming: An Essay. [Online]. Available from: https://myassignmenthelp.com/free-samples/ops910-supply-chain-analytics/additional-resources.html
[Accessed 15 July 2024].

My Assignment Help. 'Optimization Of Production Through Linear Programming: An Essay.' (My Assignment Help, 2021) <https://myassignmenthelp.com/free-samples/ops910-supply-chain-analytics/additional-resources.html> accessed 15 July 2024.

My Assignment Help. Optimization Of Production Through Linear Programming: An Essay. [Internet]. My Assignment Help. 2021 [cited 15 July 2024]. Available from: https://myassignmenthelp.com/free-samples/ops910-supply-chain-analytics/additional-resources.html.

Get instant help from 5000+ experts for

Writing: Get your essay and assignment written from scratch by PhD expert

Rewriting: Paraphrase or rewrite your friend's essay with similar meaning at reduced cost