Lorex Pharmeceuticals

Overview After reviewing your request, Cougar Consulting performed an synopsis to assist Lorex Pharmaceuticals in determining a butt surfeit rate for Linatol. The station run across that we selected is intended to increase expect ploughshare during the manufacturing process and was ground on tuition contained in a cut across given to Cougar Consulting. The analysis that we performed is expound in further detail. Current military position Even though the automatic woof chemical mechanism practiced for yield coffin nail be unsex to a proper(postnominal) bottom overindulge, the information we obtained about Linatol suggested inconsistencies in the receive measuring during operations.Since revenues and item protean greet of Linatol are directly bear upon by replete sums and contribution is the fight of these damages subtracted from revenue, ultimately, contribution is affected by the in undifferentiated fill amounts. Once we effectuate how these revenues an d hails are affected by the fill amounts, we need to particularisetle how the plectron mechanism leave function when set at a peculiar(prenominal) keister fill. These understandings give give us the information required to figure a posterior fill that maximizes contribution for Linatol.Revenue onward we realized a regularity to determine how the change mechanism functioned at a detail bell ringer fill, we had to consider how the object lens fill affected the revenues and the variable bells when cypher contribution. Starting with revenue, we learned from the score that the bottlefuls modify at or above 10 ounces would sell on the commercial grocery for $186 per guinea pig. On the other hand, bottles filled on a lower floor the advertised 10 ounces would be change for government mapping at $148. 80 per wooing and are referred to as seconds. From this information, we created a mandate ( escort 1) that metric the revenue per side as a weighted average. The s emblanceship between revenue and signal fill is shown graphically in Attachment 1 Figure 1 Revenue = (% commercial) $186/ side + (% seconds) $148. 80/ representative be As previously mentioned, calculating contribution for Linatol consists of subtracting specific variable be from revenue. The variable costs related to target fill were set in the Projected Operating clams exhibit provided to Cougar Consulting.The first cost we determined for calculating contribution was the intermingle direct labor and active ingredients. To use this cost in calculating contribution, we shared out the sum of these two costs by the total batch volume. The rounded cost of this calculation equaled $0. 4027 per ounce, and its positive linear relation to the fill amount is graphically shown in Attachment 2. In other words, the cost increases per unit as the fill amount increases per unit.Another cost needed to calculate expect contribution consisted of an extra cost associated from the event of s econds produced by the automatic filling mechanism. This additional cost is a result from the extra forwarding required by seconds and is judge from dividing the labor rate by the second of geeks the laborer can package in an hour. This cost equals $0. 7083 per case and diminishes as the fill amounts increase because a higher target fill results in slight seconds produced. This family is shown as a graph in Attachment 3.Since the cost associated for all cases is calculated in ounces, this unit was changed to cases by multiplying the cost by 12 bottles per case and a target fill amount in ounces per bottle. The additional cost per case from packaging seconds was figured by multiplying this cost by the luck of seconds created from the filling machine. This calculation will create an additional cost per case based on the number of seconds produced. The formula in Figure 2 was employ to calculate costs. Figure 2 Costs = (12 bottles/case*target fill (oz)/bottle*$0. 027/oz) + (% o f seconds) $0. 70833/case Statistical Survey Before we could determine a target fill to use for calculating maximum judge contribution, we needed to determine the probability of seconds produced by the automatic filling machine at different target fills. The best method we had to determine this probability came from the strain results provided in the make fulling-Line Test performed by Lorex. These test results were put in Exhibit 2 from the provided report and allowed us to determine the probability of seconds produced at any target fill.Assuming these take ins were chosen real at random and each sample was independent from one another, the sample entropy was analyzed and found to be genuinely evenly distributed flirt withing the fill amounts on the button varied above and at a lower place the mean and median of the entropy set. In fact, the sample fill amounts were so evenly distributed that we could use a statistical method to determine the probability of seconds prod uce by the mechanism set at a specific target fill amount. For example, with a target fill amount set at 10. 2 ounces, the method used figures that 10. 6% of the bottles will be filled less than 10 ounces, and the rest will be filled at volume adapted for commercial retail. Based on this statistical method, we created a graph (Attachment 4) to show the probability of seconds produced as the target fill amount increased. Calculating function Since we found a method to determine the probability of seconds that will be produced based on the target fill amount, we can determine a target fill that maximizes expected contribution per case because we have formulas for revenue and costs based on the expected production of seconds.The completed formula is shown below as Figure 3. Figure 3 Contribution = (% commercial) $186/case + (% seconds) $148. 80/case (12 bottles/case*target fill (oz)/bottle*$0. 4027/oz) + (% of seconds) $0. 70833/case Results The contribution formula in Figure 3 was used to determine the target fill that maximized contribution based on the probability of seconds produced. A chart was created below as Figure 4 using the formula to figure contribution at different target fills.The target fill that created the highest contribution value per case is the target fill the mechanism should be set at to maximize contribution. Attachment 5 shows the relationship between contribution per case and the target fill graphically. The graph and chart both demonstrates that the target fill should be set at 10. 4 ounces to maximize contribution. Figure 4 Target Fill (oz)Probability of Seconds Probability of CommercialContribution Per Case 912. 0523E-10$104. 60 9. 10. 999999999. 2754E-09$104. 12 9. 20. 999999712. 8665E-07$103. 63 9. 30. 999993936. 0716E-06$103. 5 9. 40. 999911588. 8417E-05$102. 67 9. 50. 999110970. 00088903$102. 22 9. 60. 993790330. 00620967$101. 93 9. 70. 969603640. 03039636$102. 37 9. 80. 894350230. 10564977$104. 74 9. 90. 734014470. 26598553$ 110. 33 100. 50. 5$118. 72 10. 10. 265985530. 73401447$127. 11 10. 20. 105649770. 89435023$132. 70 10. 30. 030396360. 96960364$135. 07 10. 40. 006209670. 99379033$135. 51 10. 50. 000889030. 99911097$135. 22 10. 68. 8417E-050. 99991158$134. 77 10. 76. 0716E-060. 99999393$134. 29 10. 82. 8665E-070. 99999971$133. 81 10. 99. 2754E-090. 99999999$133. 33 112. 0523E-101$132. 84Closing The results of this analysis were based on the data results from the Filling-Line Test and moreover apply if the filling mechanism performs consistent with these results. To ensure the filling mechanism is acting consistently with the data used for this analysis, we cheer that Lorex performs a frequent Filling-Line Test. If the data from a more recent test varies from the data used in this analysis, we also preach that Lorex requests another analysis to be performed by Cougar Consulting to determine a parvenu target fill that maximizes contribution for Linatol.