Earthmover Project: Current Project Has A Critical Path ✓ Solved

Sheet1earthmover Projectcurrent Project Has A Critical Path Of 30 Day

The current project schedule for the EarthMover project has a critical path of 30 days, which exceeds the new goal of 26 days. To meet this revised deadline, we need to identify the minimum cost crashing strategy that reduces the total project duration from 30 to 26 days while minimizing crash costs. This involves analyzing each activity's crash cost per week and crash duration limits, then applying linear programming techniques using Solver to determine the optimal crash activities.

Crashing is a project management technique where activities on the critical path are accelerated by allocating additional resources, which incurs additional costs. The goal is to shorten the project duration at the lowest possible total crash cost. Given the data for each activity—including normal durations, crash durations, crash costs, and crash limits—we can formulate an optimization problem to find the least costly crashing plan. The key steps include identifying critical activities, calculating crash costs per week, and determining feasible crash levels within activity constraints.

Sample Paper For Above instruction

In project management, the critical path method (CPM) facilitates the identification of essential activities that directly impact the project completion time. The EarthMover project's initial critical path duration is 30 days, which must be reduced to meet a new project deadline of 26 days. To achieve this, project managers utilize crashing, a technique involving compressing activity durations by allocating additional resources at increased costs. This paper explores an approach to determine the least expensive crashing strategy necessary to meet the revised deadline.

Understanding the activity data is essential. The project data includes activities labeled A through I, each with normal durations, crash durations, crash costs, and crash limits. For example, activity A normally takes 6 weeks but can be crashed to 6 weeks with no additional cost, indicating no crashing benefit. Conversely, activity H has a normal duration of 6 weeks and can be crashed down to 1 week at an extra cost of $350,000, with a maximum crash of 5 weeks. These differences necessitate prioritizing activities for crashing based on crash cost per week and crash feasibility.

The critical path analysis reveals that activities G and B are on the current critical path, with total durations summing to 30 weeks. To shorten the project by four weeks, it's logical to focus on activities with the lowest crash cost per week and the available crash potential. Calculating crash cost per week for each activity involves dividing crash costs by the number of weeks they can be shortened. For example, activity C can be crashed by one week at a cost of $50,000, resulting in a crash cost per week of $50,000. Meanwhile, activity H could be crashed up to 5 weeks at a total cost of $350,000, which equates to $70,000 per week.

Applying linear programming, using tools like Excel Solver, enables us to identify the optimal crash levels for each activity within their respective constraints to minimize total crash costs while achieving the desired project duration of 26 weeks. The decision variables include crash amount per activity, bounded by their maximum crash limits and logical limits to ensure project completion within the targeted duration.

The optimization process involves setting the objective function to minimize total crash costs, subject to constraints that ensure the total number of crash weeks reduces the project duration adequately. The constraints involve summing the crash reductions across activities such that total crash weeks sum to four weeks (from 30 to 26 days). The solution identifies specific activities to crash and to what extent, balancing crash costs and feasibility.

In conclusion, adjusting the project schedule requires a meticulous assessment of activity crash costs and limits. Using linear programming tools such as Excel Solver facilitates an optimal crashing strategy that minimizes expenditure while meeting the new deadline. Effective crashing planning ensures project success, resource optimization, and cost efficiency—integral elements in contemporary project management practices.

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