Sunday, November 10, 2019
Tastee Snax Cookies
Managerial Decision Making Led by Professor: Ocampo y Vilas Business Report Business Report MacPherson Refrigeration Tastee Snax Cookie Company By Stefanie By Stefanie Adriaenssens, Astrid de P Astrid de Paep, Soundharya Jayaraman Jayaraman, Evie Tanghe & Yudistira Sa Yudistira Sanggramawi jaya 10th Octob 17th October 2012 Antwerp M Antwerp Management School 1 Table of Contents INTRODUCTION â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦. .. 3 1PROBLEM STATEMENT â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â ¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦.. 4 2 ASSUMPTIONS & APPROXIMATIONS â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦ 4 3 SOLUTION APPROACH â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦. 5 4 RESULTS â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦ 5 WHAT-IF ANALYSIS â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦.. 6 6 OVERALL RECOMMENDATIONS â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦. 7 7 APPENDIX â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦ 8 7. 1 TABLE 1: ACTIVITIES WITH CRASHED TIME AND ADDITIONAL COSTS â⬠¦Ã¢â¬ ¦ â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦. 7. 2 TABLE 2: CPM DEADLINE INPUT 46,47 & 48 WEEKSâ⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦.. 9 7. 3 TABLE 3: CPM DEADLINE OUTPUT 48 WEEKSâ⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦ 10 7. 4 TABLE 4: CPM DEADLINE OUTPUT 47 WEEKSâ⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦ 11 7. 5 TABLE 5: CPM DEADLINE INPUT 46 WEEKS â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢ ⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦ 12 7. 6TABLE 6: RECOMMENDATIONS REGARDING CRASH TIME â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦ 13 7. 7 FIGURE 1: NETWORK OF ACTIVITIES â⬠¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦Ã¢â¬ ¦ 14 2 Introduction Tastee Snax Cookie Company is a producer of baked-goods snacks in the southeastern United States. Due to negative press reports about fat consumption and introduction of heavy advertisements of no-fat baked goods by other manufacturers, Tastee Snax Cookie Company lost a big share of the ma rket the past year.And thus, the company had to develop and manufacture no-fat cookies soon in order to secure its share in the no-fat baked goods market. The vice president of the company was made to understand by an expert that Critical Path Methodology (CPM), a project-planning scheduling technique, could be used to introduce new products in the market. He put a dynamic project manager in charge to overlook the coordination efforts of different departments in the organization to ensure that the respective assigned tasks were completed on time. In this case study, we start by addressing the problem statement of introducing a new no-fat cookie to the market.Secondly the objective is identified. Thirdly we discuss the assumptions and approximations that need to be considered before determining the solution approach. Keeping in mind the objective of the case, we then analyzed the results. Finally we present our recommendations to Tastee Snax Cookie Company. 3 1. Problem Statement The problem we address in this report is to provide an overall project plan for Tastee Snax Cookie Company to help launch their new product soon enough to gain a share in the no-fat baked goods market. This means certain ecisions will have to be made regarding the time taken to finish all activitivities while keeping the objective in mind. The objective is to determine the most cost effective method to decrease the projectââ¬â¢s deadline. The project plan discussed below has been generated through the use of a projectplanning scheduling technique, Critical Path Methodology, to secure the scientific approach. The program schedule provides a quantitative basis to make managerial decisions to shorten the implementation time of the overall project. 2. Assumptions and ApproximationsThe mathematical model created to schedule all the projects is based upon a number of simplifying assumptions and approximations. These need to be taken into account in order to make an independent judgment ab out the modelââ¬â¢s usefulness. The assumptions and approximations of this model are: ? The product introduction program has been broken down into three groups of activities: Research & Development, Marketing & Advertising, and Promotion; ? The description of each activity and the indicated time required for its completion in weeks was taken at face value from the case; The tasks to be performed by each department and the estimated durations and deadlines were also considered as given; ? The preceding activities for each activity are considered as such; ? The tasks that could potentially be ââ¬Å"crashedâ⬠by increasing resources were decisions based on the information available in the case. 4 3. Solution Approach The problem has been modeled into Critical Path Methodology (CPM). The CPM approach is based on a network representation that reflects activity precedence relations.As shown in Figure 1, the nodes designate activities and their time duration, and the arcs define t he precedence relations between the activities. The Earliest Start (ES) and Earliest Finish time (EF) for each activity is calculated as shown below. ES = Maximum EF of all its immediate predecessors EF = ES + (Activity completion time) ES and EF are represented on the CPM network by a pair of numbers, in black, above the node representing the activity. Subsequently, the Latest start time (LS) and Latest finish time (LF) was determined for each activity which allows the project to be completed by its minimal completion date.LS and LF was calculated as shown below. LS and LF are represented as a pair of numbers, in red, in CPM network. LF = Minimum LS of all immediate successor activities LS = LF ââ¬â (Activity Completion Time) Based on the information available in the case on slack time in weeks for each activity, the critical path of the model was deduced. A critical path has activities with zero slack and is the longest path in the network. A delay in one of the activities of the critical path results in a delay of the overall project. As can be seen in figure 1, the earliest and latest times are the same in the activities of the critical path. 4. ResultsBased on the CPM network drawn we have deduced the following for each activity: Earliest Start (ES), Earliest Finish Time (EF), Latest Start time (LS) and Latest Finish time (LF) (see Figure 1). The maximum of EF times, 52 weeks, is the estimated completion of the entire project. By taking into consideration the slack times in weeks provided in the case, we then arrived at the critical path. The critical path contained the critical activities with zero slack time. Critical Path: B1-A2-B5-B6-A4-A5-B9-B11-A6-A7-A8 5 5. What-if Analyses The following paragraph discusses additional economical and operational information as provided in the case.The earlier a product would enter the market the quicker it would be able to gain market share. This motivated the Project Manager to develop a list of tasks that coul d be potentially ââ¬Å"crashedâ⬠by increasing resources allocated to them (see Table 1). In Table 1, you will find this list of activities that could be performed faster by increasing the cost of operations. According to the crashing analysis, the cheapest way to shorten the project duration by four weeks is to crash three activities. As seen in Table 3 activity A4 should be crashed three weeks and activities B2 and B5 one week.The additional cost to reduce the project duration from 52 weeks to 48 weeks is $7,200. The cheapest way to shorten the project duration by five weeks is to crash four activities. As seen in Table 4 activity A4 should be crashed three weeks and activities A7, B2 and B5 one week. The reduction of the project duration by five weeks costs an additional $ 10,700. The CPM analysis shows that the cheapest way to shorten the project duration by six weeks is to crash four activities. As seen in Table 5, activity A4 should be crashed by three weeks, activity A7 by two weeks and activities B2 and B5 by 1 week.To reduce the project duration by six weeks, the additional cost adds up to $ 14,200. 6 6. Overall Recommendations The objective of the model was to find a solution to shorten the implementation. That is, to determine the most cost effective way to decrease the projectââ¬â¢s timeline, which would help Tastee Snax Cookie Company to launch their new product and thereby capturing a market share in the no fat baked foods market. Based on our results, we would state that the maximum number of weeks by which the project can be shortened is 6 weeks.To calculate this, the activities A4, A7, B2 and B5 are crashed resulting the Earliest Finish time (EF) of 46 weeks for the project (See Table 6). Activities A4, A7 and B5 are crashed to their maximum crashed time. The additional cost for crashing the project to 46 weeks can be determined with solver, as already explained in the report, which is $14,200. Hence we recommend that the optimal solu tion would be to reduce the project duration by 6 weeks at an additional cost of $14,200. 7 7. Appendix 7. 1 Table 1: activities with crashed time and additional cost Activity Develop special Crashed Time Additional Cost Weeks) A3 Original Time (Weeks) ($) 5 3 2200 6 3 3900 6 4 7000 10 8 3200 4 3 1700 4 3 3000 equipment list A4 Prepare manufacturing specifications A7 Receive and install equipment B2 Develop and test packaging and product names B5 Perform taste test B6 Review results and choose products 8 7. 2 Table 2: CPM Deadline Input 46, 47 & 48 weeks 46/47 48 PROJECT DEADLINE = IMMEDIATE PREDECESSORS ACTIVITY A1 A2 A3 A4 A5 A6 A7 A8 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 C1 C2 C3 C4 C5 NODE NORMAL TIME A B C D E F G H I J K L M N O P Q R S T U V W X Y 2 5 5 6 4 1 6 6 3 10 10 3 4 4 7 4 8 4 5 8 5 4 1 5 6 NORMAL COST CRASHTIME 2 5 3 3 4 1 4 6 3 8 10 3 3 3 7 4 8 4 5 8 5 4 1 5 6 CRASH COST 2200 3900 7000 3200 1700 3000 NODE PREDECESS OR B B C D D E F F G H J K L M M N P P P Q Q Q R S T T U V A I B C N D D S F G I J I B L M O X Y E K P Q Q R S I U W X X Y Y U J W J V 9 7. 3 Table 3: CPM Deadline Output 48 weeks CRASHING ANALYSIS 7200 TOTAL PROJECT COST 48 COMPLETION TIME ACTIVITY A1 A2 A3 A4 A5 A6 A7 A8 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 C1 C2 C3 C4 C5 PROJECT NORMAL COST 0 PROJECT CRASH COST 21000 NODE Completion Time Start Time Finish Time Amount Crashed Cost of Crashing Total Cost A B C D E F G H I J K L M N O P Q R S T U V WX Y 2 5 5 3 4 1 6 6 3 9 10 3 3 4 7 4 8 4 5 8 5 4 1 5 6 1 3 10 15 18 35 36 42 0 3 12 5 8 11 11 18 22 31 30 35 3 8 12 13 12 3 8 15 18 22 36 42 48 3 12 22 8 11 15 18 22 30 35 35 43 8 12 13 18 18 0 0 0 3 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3900 0 0 0 0 0 1600 0 0 1700 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3900 0 0 0 0 0 1600 0 0 1700 0 0 0 0 0 0 0 0 0 0 0 0 10 7. 4 Table 4: CPM Deadline Output 47 weeks CRASHING ANALYSIS 10700 TOTAL PROJECT COST 47 COMPLETION TIME ACTIVITY A1 A2 A3 A4 A5 A6 A7 A8 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 C1 C2 C3 C4 C5 PROJECT NORMAL COST 0 PROJECT CRASH COST 21000 NODE CompletionTime Start Time Finish Time Amount Crashed Cost of Crashing Total Cost A B C D E F G H I J K L M N O P Q R S T U V W X Y 2 5 5 3 4 1 5 6 3 9 10 3 3 4 7 4 8 4 5 8 5 4 1 5 6 1 3 10 15 18 35 36 41 0 3 12 5 8 11 11 18 22 31 30 35 3 8 12 13 12 3 8 15 18 22 36 41 47 3 12 22 8 11 15 18 22 30 35 35 43 8 12 13 18 18 0 0 0 3 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3900 0 0 3500 0 0 1600 0 0 1700 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3900 0 0 3500 0 0 1600 0 0 1700 0 0 0 0 0 0 0 0 0 0 0 0 11 7. 5 Table 5: CPM Deadline Output 46 weeks CRASHING ANALYSIS 14200 TOTAL PROJECT COST COMPLETION TIME ACTIVITY A1 A2 A3 A4 A5 A6A7 A8 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 C1 C2 C3 C4 C5 A B C D E F G H I J K L M N O P Q R S T U V W X Y 21000 Start Time Finish Time Amount Crashed Cost of Crashing Total Cost 1 3 10 15 18 35 36 40 0 3 12 5 8 11 11 18 22 31 30 35 3 8 12 13 12 3 8 15 18 22 36 40 46 3 12 22 8 11 15 18 22 30 35 35 43 8 12 13 18 18 0 0 0 3 0 0 2 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3900 0 0 7000 0 0 1600 0 0 1700 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3900 0 0 7000 0 0 1600 0 0 1700 0 0 0 0 0 0 0 0 0 0 0 0 46 NODE Completion Time 2 5 5 3 4 1 4 6 3 9 10 3 3 4 7 4 8 4 5 8 5 4 1 5 6 0 PROJECT NORMAL COST PROJECT CRASH COST 12 7. Table 6: Recommendations regarding crash time Activity Required Time Crashed Time ES EF A1 2 ââ¬â 0 2 A2 5 ââ¬â 3 8 A3 5 3 8 11 A4 6 3 15 18 A5 4 ââ¬â 18 22 A6 1 ââ¬â 35 36 A7 6 4 36 40 A8 6 ââ¬â 40 46 B1 3 ââ¬â 0 3 B2 10 8 3 11 B3 10 ââ¬â 11 21 B4 3 ââ¬â 3 6 B5 4 3 8 11 B6 4 3 11 15 B7 7 ââ¬â 0 7 B8 4 ââ¬â 17 21 B9 8 ââ¬â 22 30 B10 4 ââ¬â 30 34 B11 5 ââ¬â 30 35 B12 8 ââ¬â 35 43 C1 5 ââ¬â 3 8 C2 4 ââ¬â 8 12 C3 1 ââ¬â 8 9 C4 5 ââ¬â 11 16 C5 6 ââ¬â 11 17 13 7. 7 Figure 1: The network of activities It visualises the predecessor relationships, the early start and finish times (black) and the latest start and finish time (red). Nodes and bars in green visualize the critical path.
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