Process Optimization
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Optimizing Travel

                Process optimization can initially seem overwhelming due to the many facets involved.  However, if each aspect is broken down, it can actually become a simple system.  Below is a simple example of the use of process optimization.  The situation is a common commute from work to home during peak driving hours.  The current method is leaving work and driving home at 5:00 in the afternoon.  While this method wastes no time between leaving work and driving home, it presents the issue of encountering traffic and all of the troubles associated.  Therefore, the method of process optimization can be applied in order to determine the most productive situation.   

                The first step in process optimization is problem identification.  The actual problem must be identified before attempting to address it.  Basically, it is necessary to know what is being looked for before attempting to look.  In the case of the commute, the situation is a rush hour commute.  The question involved is how the commute can be improved.  In order to address this question, possibilities must be proposed and individually validated based on qualifications.  This will result in the identification of the problem.  Below are several suggestions and their supporting or opposing factors: 

 

Can the traffic be changed? 

                -At 5:00, traffic will be present at all routes 

Can an alternative transportation method be used? 

                -Due to the distance and number of passengers, a family-size car is the only choice 

Can an alternative route be used? 

                -All routes possible will have traffic 

Can an alternative leaving time be made? 

                -Cant leave earlier but can leave later 

 

From these choices, it can be evaluated that the only possible solution is to change the time of leave.  Therefore, the problem has been identified to be what the best time to leave is.   

                With the problem identified, important test factors have to be assigned to evaluate the best time.  The idea is to leave at the optimal time.  However, it must be stipulated as to what the optimal time is in regards to.  Possible considerations are: 

 

-time loss 

-vehicle wear 

-accident risk 

-travel costs 

-amount of productivity 

 

                While it would be ideal to consider all of these matters, it would be very difficult to focus on each one at the same time.  Therefore, they must be ranked based on importance and manipulability.  The most important three in this case will be time loss, travel costs, and vehicle wear in that order.  Also, factors which will be affected in each case also need to be defined.  While time loss is almost completely governed with the leave time, travel costs and vehicle wear can be affected by three factors: breaking, acceleration, and engine temperature.  The amount and intensity of each factor can be evaluated in order to assign values to travel cost and vehicle wear.  The definition of these factors outlines the testing parameters required for scenario evaluation.   

                The next step in process optimization for this situation is data collection.  Using the outlined parameters, a series of data points are taken in correlation to varying leave times.  This data is taken over a specified amount of time which is determined statistically.  The data is then tabled and displayed graphically as well as evaluated using various statistical approaches.  In this case, a visual table will be used to evaluate the times.   

                As seen in the figure, there are multiple points where peaks are present.  Using the order of importance, a peak is identified which represents the optimal leave time.  This concludes the determination of leave time.  While this is only one aspect of the drive, many other factors can be analyzed during the commute in order to perform a more thorough process optimization.  Factors include speed during the drive, weight present in the car, and various internal conditions.  In realistic situations, more aspects of the process must be consulted in order to accomplish a full process optimization. 
 

See Travel Time Optimization Write-Up