Management Science and Operation Planning

Management Science and Operation Planning Order Description This coursework requires me to build a simulation model to identify the best configurations for the National Cranberry Coorperative case study(can be found online). The key part to this assignment is the simulation model built using Excel, the report is only to explain the approach and recommendation to the company for improvements. Therefore, no reference needed. Thank you very much for the Excel model I am really struggling with it. also explain in details in other attachment explaining the how to build the Excel model so I can learn from it? National Cranberry Cooperative Session 2 Dr. Maurizio Tomasella University of Edinburgh Business School [email protected] Thursday, November 20, 2014 . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 1 Outline Session 2: Analysis Preparation for Session 3 . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 2 Flowchart of process berries at RP1 . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 3 RP1 Inventory build-up diagram (process berries) . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 4 Impact of new dryers on berry processing time ? clearly, the purchase of additional drying capacity will enable NCC to cut overtime costs of RP1 ? it should also help to cut truck waits ? let’s focus a bit more on overtime savings, for the moment ? .... how many dryers can be justified, just on the basis of overtime savings? . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 5 Impact of new dryers on berry processing time ? if you repeat the reasoning we did in class, and try to quantitfy the benefits from a first additional dryer, a second additional dryer, and so on, and reuse the learnings from both the process flowchart and the inventory build-up diagram, you will get to numbers that are similar to those in the next slide . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 6 Impact of new dryers on berry processing time . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 7 Impact of new dryers on berry processing time Lessons learned: ? ? no. 1: the marginal benefits from additional drying units decrease consderably after the first one (decreasing marginal returns) no. 2: on a peak day (19,000 bbls/day coming in, according to my numbers), with two dryers (drying capacity 1,000 bbls/hour), the bottleneck for the overall process becomes separation/milling (which can do at most 1,200 bbls/hour in total, i.e. “dry+wet” berries) ? bottlenecks indeed float from point to point in the same process, depending on conditions !!! . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 8 Take-Aways from Analysis ? conceptual take-aways ? ? ? bottlenecks decreasing marginal returns basic tools for process analysis ? ? process flowchart (flow diagram) inventory build-up diagram . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 9 Preparation for Session 3 Back at NCC, it is now 3rd March 1977. Since last year, the wet berry harvesting technique has taken over the entire fall harvest so that processing dry berries is no longer an issue for management. RP1 expects to take in this fall 19,200 bbls of wet berries on each of 10 (and only 10) expected peak days. A peak day starts with the first truck arriving at 0700 and ends with the last truck arriving just before 1900. . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 10 Preparation for Session 3 The plant now has 5 dryers capable of processing 200 bbls/hour each, and an upgraded jumbo separator that can process 2,400 bbls/hour. The wet bin capacity is 3,200 bbls of berries. Additionally, as many as 14 dry bins (now unutilized) can be converted to hold wet berries. Each of these bins has a capacity of 250 bbls. . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 11 Preparation for Session 3 ? How much truck wait (valued in US $) might be expected on a peak day this year? ? What should the plant do to remedy the situation? Your objective is to incur low cost, defined as the sum of investment and truck-wait costs (ignore overtime and other costs) for this year. All truck-wait comes from the 10 peak days of this year. . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 12 Preparation for Session 3 Truck wait is valued at $200 per hour and the average truck could hold 90 bbls. New dryers, each able to process 200 bbls/hour, cost $64,000 each and a bin conversion costs $7,000. . ional Cranberry Cooperative Session 3 Dr. Maurizio Tomasella University of Edinburgh Business School [email protected] Monday, November 24, 2014 . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 1 Outline Session 3: Analysis 2nd Coursework . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 2 Problem Formulation . min new ,N Ndryer conv new TC = 103 · (7 · Nconv + 64 · Ndryer )+ subject to 200 · A 9 ? ?0 2 new )-(3200+250·N A = [2400·(3-Ndryer conv )] ? new )(5+N 50(3-Ndryer conv ) if m = l if m > l [ ( )] new m = 12 · 10 1.6 - 0.2 · 5 + Ndryer 3 l = 103 · [3.2 + 0.25 · Nconv ] Nconv = 14 new Ndryer =7 new Nconv , Ndryer =0 new Nconv , Ndryer ?N (1) . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 3 2nd Coursework Still at NCC, let us take our clock back to the early Spring of 1971. The decision of buying one additional dryer has just been made and an order for the equipment placed. While this will relieve RP1’s overtime problems, it is not quite clear that it will necessarily be helpful in solving the truck queueing problems. Although fewer waiting trucks could be expected on ‘extreme’ peak days, most of the days in the season are either non-peak or ’average’ peak days. Hence even fewer waiting trucks should be expected in these less problematic days, if compared to the three-dryers configuration at the start of year 1971. Normally, then, the queueing problems should also be ‘solved’ with one extra dyer. . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 4 2nd Coursework However: ? berries (trucks) do not arrive evenly spaced during the day ? which is a major simplifying assumptions we’ve been making so far throughout our discussions and analyses of the case ? percent of wet berries will not remain constantly equal to 70% every day ? the total number of trucks arriving in a day is not known with 100% certainty before the day starts ? the load of berries in a single truck is not constant . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 5 2nd Coursework Assume you are one of the farmer-owners of the coop, and, as such, you are particularly sensible to truck waiting costs. ? How many dryers would you buy now to get prepared for this coming fall, if the decision was entirely up to you? Would one extra dryer be enough? ? Would you convert any of the dry berry storage bins into wet storage bins? If yes, how many? ? Would you modify the work force schedules at RP1? If yes, how? Quantify benefits of any combination of the above levers (i.e. one combination of your choice), in terms of savings in truck waiting, using discrete event simulation. Compare this to the starting configuration (i.e. the one described in the 11-page case study). . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 6 2nd Coursework Write up your work in a short report, containing: ? the description of your approach to simulation modelling, as well as any assumptions you made ? the discussion of results from your simulation analysis your final recommendations to NCC, in terms of ? ? ? ? number of extra dryers to buy (if any) number of storage bin conversions (if any) work force scheuling rearrangements (if any) Organise your report as you prefer, but write it as if you were to submit it to your line manager as a formal deliverable of a company project. Remember that this is an individual project, not group work! . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 7 2nd Coursework Length of the report: ? no more than ten pages in length, all included (tables, figures, appendices, etc.) ? no more than 2,000 words, again all included In your report, you should use the language of discrete event simulation you learned from MSOP lectures (module 1) and used in both the related tutorial and lab. Your ability to condense information clearly in tables/figures of your own production, instead of long paragraphs of text, is not only appreciated but will generally lead to higher marks than a verbose content that is di?cult to decipher. . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 8 2nd Coursework Software requirements: ? you can only use Microsoft Excel as the sw for this assignment ? if you don’t submit your Excel files alongside the report, it will be in general impossible for the markers to reproduce exactly your results, so do NOT forget to submit your Excel files! ? however, your report should be 100% self-contained, i.e. I should be able to understand everything (assumptions, analysis, calculations in Excel if any, final recommendations, etc.) WITHOUT having to open your Excel files! ? i.e. your Excel files should only be a back-up for me and the second marker to use only to check if the numbers in your report are ‘true’, or to check anything not clear form the text. ? if you think this helps, please refer to your Excel files in the text (with precise references), to help us check your calculations. . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 9 On Session 4 . . . ? start to work on your 2nd Coursework before Session 4 ? bring anything you have been able to do for your 2nd coursework to Session 4 ? In Session 4, I will answer any questions you may have on the 2nd coursework (main activity of the session) ? In Session 4, I will also build further links between real problems such as the one at NCC/RP1 and how simulation based techniques can be used in practice to tackle these problems . .. .. . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . .. . . . . .. .. .. 10 Harvard Business School 9-675-014 W Rev. November 16, 1983 National Cranberry Cooperative On February 14, 1971, Hugo Schaeffer, vice president of operations at the National Cranberry Cooperative (NCC), called his assistant, Mel O'Brien, into his office and said: (0 Mel, I spent all day yesterday reviewing last fall's process fruit operations at g receiving plant No. 1 [RP1] with Will Walliston, the superintendent, and talking with the co-op members [growers] in that area. It's obvious to me that we haven't solved E _ 9) our problems at that plant, yet. Even though we spent $75,000 last winter for a fifth Kiwanee dumper at RP1, our overtime costs were still out of control this fall, and the g 3 growers are still upset that their trucks and drivers had to spend so much time waiting to unload process fruit into the receiving plant. I can't blame them for being upset. They are the owners of this cooperative, and they resent having to lease trucks g 5 @g) and hire drivers to get the berries out of the field and then watch them stand idle, waiting to unload. IE ‘3 g 7‘18 8 Walliston thinks that the way to avoid these problems next fall is to buy and install two new dryers [$25,000 each], and to convert our dry berry holding bins so 5&2 that they can be used to store either water-harvested or dry berries [$5,000 per bin]. I i want you to go out there and take a hard look at that operation and find out what we need to do to improve operations before the 1971 crop comes in. We're going to have 8'; g to move quickly if we are going to order new dryers, since the equipment and 3:: installation lead times are in excess of six months. By the way, the growers in that 8%2 region indicated that they plan on about the same size crop this year as last. But it looks like the percentage of water-harvested berries this year will increase to 70% of total process fruit from last year's 58%. NCC and the Cranberry Industry ESE NCC was an organization formed and owned by growers of cranberries to process and §F% market their berries. In recent years 99% of all sales of cranberries were made by the various E cooperatives that are active in the cranberry industry. NCC was one of the larger cooperatives and 8 had operations in all the principal growing areas of North America: Massachusetts, New Jersey, LE Wisconsin, Washington, Oregon, British Columbia, and Nova Scotia. Table A contains industry data 5 for US. production and sales of cranberries. This case represents a major revision of the ease "American Cranberry Cooperative", written by ]. Tucker. It was prepared as the basis for Class discussion rather than to illustrate eflectioe or inefl'eetive handling of an administrative situation. Copyright © 1974 by the President and Fellows of Harvard College. To order copies or request permission to reproduce materials, call 1-800-545-7685 or write Harvard Business School Publishing, Boston, MA 02163. No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means-electronic, mechanical, photocopying, recording, or otherwise-without the permission of Harvard Business School. Distributed by The Case Centre North America Rest of the world rc:sseercl:ld"eiorg Z idf:.i::@3?h:i::ecentre.org Z iriggtjiiéfisiizfénrg PLACE THIS ORDER OR A SIMILAR ORDER WITH US TODAY AND GET AN AMAZING DISCOUNT :)