As more research and technology is advancing in the medical field today, there are many more choices in the treatment of cancer. The decision on the type of treatment is very important because it is someone's life on the line. So how does a cancer patient decide the right route to take?
What may help a cancer patient is a decision support system. A decision support system can help inform the user of other treatments and medications that the patient may have been unaware about. In an article, $2 million is dedicated for the combination of research initiatives and a national website that is aimed to match breast cancer patients with clinical trials nationwide and even provide decision support tools.
How the DSS will help the patient is by allowing the user to come out the DSS fully informed and confident with his/her decision. The data base will have the the different types of breast cancer, stages of cancer, cancer information, treatment types and information, medication, support group information, prosthesis retailers, and doctors that specialize in cancer treatment and related fields.
The user will be prompted to choose why they are visiting the site and go straight to the needed decision support tool or go through a formalized system of questions. Information and links will be tied to certain questions such as if a patient has a mascetomy, links to reconstruction and prothesis will be provided by the side. Also, the patient can view side effects of certain medications and treatments while using the DSS. If the patient is unfamiliar with what steps to take, the DSS will guide her linearly through the menu and questions. If a professional is using the DSS such as a doctor, the doctor can input certain conditions so that the database can match those conditions to the right treatment.
References
De Gier, Vanessa. Safeway Foundation Gives $2 million to UCSF for Breast Cancer Support. University of California, San Francisco. 30 April 2008.
http://pub.ucsf.edu/newsservices/releases/200804301/
Wednesday, April 30, 2008
Wednesday, April 23, 2008
Blog 10: Should Companies "Go Green" by Recycling?
The recent trend is building to recycle. Many companies may still think that implementing "earth-saving techniques and methods" may cost them more, but maybe that is just an misconception.
In fact, manufacturing plants in particular can save costs by recycling scraps. Costs that would have incurred if plants did not recycle are - disposal fees, additional material purchases, labor to rid the piles of waste, and an overall less friendly environment.
To analyze the problem, a decision support system can be designed by allowing the user to design a plant layout with the ability to reproduce production processes through historical data and forecasts. Historical data can also represent the average amount of scraps from each part produced and packaged. In addition, potential savings are instant if items are easily recyclable. However, what can't be modeled are employees' attitudes towards the recycling program. Perhaps a survey can be used to know the majority of employee's attitudes towards the recycling implementation. Incentives such as a $25 gift certificate or half day off if a certain recycling quota is met (i.e. 800 lbs of recycled paper within 1 week is the projected goal) will be given to employees for motivation and cooperation for the implementation of the program.
If companies start utilizing decision support systems in deciding implementation for recycling, then maybe more companies might realize that recycling may even reduce costs.
References
Manufacturers achieve scrap recycle targets. Environmental Transport Association (ETA). 21 April, 2008. Retrieved April 21, 2008 from http://www.eta.co.uk/node/10487.
In fact, manufacturing plants in particular can save costs by recycling scraps. Costs that would have incurred if plants did not recycle are - disposal fees, additional material purchases, labor to rid the piles of waste, and an overall less friendly environment.
To analyze the problem, a decision support system can be designed by allowing the user to design a plant layout with the ability to reproduce production processes through historical data and forecasts. Historical data can also represent the average amount of scraps from each part produced and packaged. In addition, potential savings are instant if items are easily recyclable. However, what can't be modeled are employees' attitudes towards the recycling program. Perhaps a survey can be used to know the majority of employee's attitudes towards the recycling implementation. Incentives such as a $25 gift certificate or half day off if a certain recycling quota is met (i.e. 800 lbs of recycled paper within 1 week is the projected goal) will be given to employees for motivation and cooperation for the implementation of the program.
If companies start utilizing decision support systems in deciding implementation for recycling, then maybe more companies might realize that recycling may even reduce costs.
References
Manufacturers achieve scrap recycle targets. Environmental Transport Association (ETA). 21 April, 2008. Retrieved April 21, 2008 from http://www.eta.co.uk/node/10487.
Wednesday, April 16, 2008
Blog 9: Earthquake Prediction and the Effect on Decision Makers
Natural disasters can greatly impact a supply chain by sending it to a halt. When earthquakes occur, supply chain specialists need to know how to respond and be proactive prior to the earthquake. But if an earthquake is a natural disaster, how is it accurately predicted? To predict an earthquake, a scientific-detailed model is used to forecast the natural disaster.
First, the model needs the most current, up-to-date geological and seismological data. In addition, historical patterns must be examined as well as major fault lines. From here, these results include the degree of earthquake magnitudes and its effect on the land. These results can greatly impact supply chain decisions such as where to locate a facility (obviously-not on a major fault line!), and if products are expensive-don't locate a warehouse in a high-risk earthquake area. Although, many may think a computerized earthquake model is irrelevant, it can greatly affect any business decision. As a result, a simulation model should include forecast models for earthquakes so that businesses can maintain a resilient supply chain.
References
Bowles, Jennifer. California Earthquake Probability Study Rejiggers Inland Causes for Concerns. 15 April, 2008. ARN. Retrieved April 15, 2008 from http://www.blogger.com/post-edit.g?blogID=3961439252729962199&postID=4748261664757262560.
First, the model needs the most current, up-to-date geological and seismological data. In addition, historical patterns must be examined as well as major fault lines. From here, these results include the degree of earthquake magnitudes and its effect on the land. These results can greatly impact supply chain decisions such as where to locate a facility (obviously-not on a major fault line!), and if products are expensive-don't locate a warehouse in a high-risk earthquake area. Although, many may think a computerized earthquake model is irrelevant, it can greatly affect any business decision. As a result, a simulation model should include forecast models for earthquakes so that businesses can maintain a resilient supply chain.
References
Bowles, Jennifer. California Earthquake Probability Study Rejiggers Inland Causes for Concerns. 15 April, 2008. ARN. Retrieved April 15, 2008 from http://www.blogger.com/post-edit.g?blogID=3961439252729962199&postID=4748261664757262560.
Wednesday, April 9, 2008
Blog 8: Where do you want to live?
As a
To model the best place to live, there would be a database of top 150 cities based on population and attractions (150 is just a recommended cut-off). These cities are then divide into three categories such as large cities, medium cities, and small cities with a population range for each category, in which CNN did not take city size into consideration. The database will then have standard characteristics that are assigned to each city such as types of attractions: trout fishing, surfing, American battleground, Indian reservation, and attractions as such. In addition, other city characteristics such as climate, unemployment level, affordable housing, architectural styles, proximity to certain landmarks, and number of businesses' corporate headquarters are taken into consideration. The user will choose what factors are important to them, and the places with the most matches will show up as the best places to live. Also, the user can choose points on a map, where the decision support system can calculate the center of gravity and match the closest top-city as the best place to live. This DSS should also have current or real-time data since cities are constantly growing and changing.
This DSS can help individuals each time they want to relocate. Relocation is due to many reasons: college graduation, divorce, career change, or other reason.
ReferencesMoney Magazine's Best Places to Live. CNNmoney.com. Retrieved April 9, 2008 from http://money.cnn.com/magazines/moneymag/bplive/2007/top100/
Wednesday, April 2, 2008
Blog 7: Opening a Shopping Center
The grand opening is finally announced for the Orchad Town Shopping Center! This shopper center is an outdoor center with nearly one million square feet of stores, restaurants, and attractions. Although there are malls are being erected regularly in developing areas, there usually is a little more to it.
When opening a new shopping mall, many efforts and analyses are considered before actual implementation. To forecast the success of the mall, a decision maker may hire a consultant to create a simulation model.
The simulation model can predict demand for the shopping mall based on attractiveness, such as square footage, how much demand it can grab from other potential competitors, and the distance from consumers.
However, other qualitative factors may affect the shopping center's success as well. The attractiveness may not be the size of the shopping center, but rather the actual stores and specialties that the new place offers. In addition, the decision making team must look at demographics within the area such as age, gender, and household income. The amount of traffic passing through the location may also be an important factor. Nevertheless, the cost of land may be too high and business may not be successful.
The simulation model can predict the demand and find a center of gravity to help decision makers pick a feasible location with potential positive profit margins. Although the center of gravity is a heuristic and can not find the optimal location, the center of gravity helps decision makers by centering itself based on weighted customer demand. From here, decision makers can find a location close to the center of gravity.
Although the simulation results may find high demand and a great location for the shopping center, other factors (as mentioned before) such as demographics, traffic amount, and cost of land are things to also think about before implementation.
References
Grand opening set for Orchard Town Center. Denver Business Journal. 2 April, 2008. Retrieved April 2, 2008 from http://www.bizjournals.com/denver/stories/2008/03/31/daily48.html
When opening a new shopping mall, many efforts and analyses are considered before actual implementation. To forecast the success of the mall, a decision maker may hire a consultant to create a simulation model.
The simulation model can predict demand for the shopping mall based on attractiveness, such as square footage, how much demand it can grab from other potential competitors, and the distance from consumers.
However, other qualitative factors may affect the shopping center's success as well. The attractiveness may not be the size of the shopping center, but rather the actual stores and specialties that the new place offers. In addition, the decision making team must look at demographics within the area such as age, gender, and household income. The amount of traffic passing through the location may also be an important factor. Nevertheless, the cost of land may be too high and business may not be successful.
The simulation model can predict the demand and find a center of gravity to help decision makers pick a feasible location with potential positive profit margins. Although the center of gravity is a heuristic and can not find the optimal location, the center of gravity helps decision makers by centering itself based on weighted customer demand. From here, decision makers can find a location close to the center of gravity.
Although the simulation results may find high demand and a great location for the shopping center, other factors (as mentioned before) such as demographics, traffic amount, and cost of land are things to also think about before implementation.
References
Grand opening set for Orchard Town Center. Denver Business Journal. 2 April, 2008. Retrieved April 2, 2008 from http://www.bizjournals.com/denver/stories/2008/03/31/daily48.html
Wednesday, March 19, 2008
Blog 6: Auto Plant Simulates its Production System
Background
The Nissan Motor Manufacturing plant in the United Kingdom needed to optimize production processes for Nissan's new Qashqai model, a sport utility vehicle with a unique look. The Nissan plant considered two options, either the traditional industrial engineering methods or the use of a simulation model.
Which solution-manual calculations or simulation software?
The traditional manual calculation method included "calculations determining the capacity using a planned system efficiency percentage" and creation of production charts. Manual calculations are too time consuming, in which requires more labor costs, and has a higher risk of errors.
Nissan found that the simulation approach was better suited since the analysis is more in-depth. First, the simulation model software created a scenario for each smaller production cell in the line to improve process times. After the smaller cells were improved, the Nissan team produced a large-scale model with all the smaller production cell data combined.
Possible Data for the Simulation
Possible data for the simulation analyses are machine processing times, capacity of machine and labor, idle time (if applicable), number of machines available, demand for the product, number of workers available, batch sizes, and probability of defects. Qualitative data needed may be the condition of the machinery, worker motivation, and order of tasks. Nissan may also keep in mind lead times and shipment times that affect its customer service levels.
What kind of results does Nissan want?
Nissan probably wants faster processing times, increased capacity, eliminated/reduced idle time, improved quality, and a low defect number. Each individual model should be analyzed before moving on to the large-scale model for analysis.
How are simulation models helpful?
Simulation models have helped Nissan by providing a visual, interactive, and dynamic aid to decision makers. Nissan doesn't have to shut down its plant just to test a new methodology or process, decision makers can change variables and scenarios in the simulation model to represent the real-life process. In addition, simulation models can help improve the production capacity due to the growing demand for the Qashqai model.
Unlike manual calculations, simulation models replicate calculations easily by just a few clicks. Where as in a hand simulation, calculations need to be completed from step one. By modeling scenarios, Nissan can find more feasible solutions for their production processes.
References
Car plant simulates production systems. Manufacturingtalk. 17 March, 2008.Retrieved March 19, 2008 from
http://www.manufacturingtalk.com/news/lan/lan111.html
The Nissan Motor Manufacturing plant in the United Kingdom needed to optimize production processes for Nissan's new Qashqai model, a sport utility vehicle with a unique look. The Nissan plant considered two options, either the traditional industrial engineering methods or the use of a simulation model.
Which solution-manual calculations or simulation software?
The traditional manual calculation method included "calculations determining the capacity using a planned system efficiency percentage" and creation of production charts. Manual calculations are too time consuming, in which requires more labor costs, and has a higher risk of errors.
Nissan found that the simulation approach was better suited since the analysis is more in-depth. First, the simulation model software created a scenario for each smaller production cell in the line to improve process times. After the smaller cells were improved, the Nissan team produced a large-scale model with all the smaller production cell data combined.
Possible Data for the Simulation
Possible data for the simulation analyses are machine processing times, capacity of machine and labor, idle time (if applicable), number of machines available, demand for the product, number of workers available, batch sizes, and probability of defects. Qualitative data needed may be the condition of the machinery, worker motivation, and order of tasks. Nissan may also keep in mind lead times and shipment times that affect its customer service levels.
What kind of results does Nissan want?
Nissan probably wants faster processing times, increased capacity, eliminated/reduced idle time, improved quality, and a low defect number. Each individual model should be analyzed before moving on to the large-scale model for analysis.
How are simulation models helpful?
Simulation models have helped Nissan by providing a visual, interactive, and dynamic aid to decision makers. Nissan doesn't have to shut down its plant just to test a new methodology or process, decision makers can change variables and scenarios in the simulation model to represent the real-life process. In addition, simulation models can help improve the production capacity due to the growing demand for the Qashqai model.
Unlike manual calculations, simulation models replicate calculations easily by just a few clicks. Where as in a hand simulation, calculations need to be completed from step one. By modeling scenarios, Nissan can find more feasible solutions for their production processes.
References
Car plant simulates production systems. Manufacturingtalk. 17 March, 2008.Retrieved March 19, 2008 from
http://www.manufacturingtalk.com/news/lan/lan111.html
Wednesday, March 12, 2008
Blog 5: A Simple Model in Finding Stock Value
Situation
The article, US Airways Shares Fall as JPMorgan Downgrades Airline Stocks, discusses the decrease in airline stock prices such as Tempe and other large airlines. Due to rising fuel prices and a weakening economy, Standard & Poor's Ratings Services plan to review the top ten US airline companies. For example, "US Airways stock closed at $9.98 per share Tuesday and dipped to $8.87 Wednesday before starting a rebound to end the day at $9.44 (Luebke 2007)."
Who is Affected?
Stock holders with risky stock such as the airline industry need to know when to buy in the market and when to sell their stock. In this situation, the main decision makers in this situation are stock holders such as the corporation and individuals.
What Model Should be Used?
A simple financial model known as the Dividend Discount Model (DDM). DDM tells you the value of equity, which is stock. Three variables are needed to determine the current value/price of stock. First, the dividend amounts are needed for a base period and for the following period after that. Second, the percentage of total expected return by investors (current income + price change), which is defined as variable R. Third, the annual growth rate from the base period and the next period is needed, which is defined as variable G. To find the stock's price, divide the next period's dividend amount by R minus G as so:
Price of Stock = Dividend of Next Period
__________________
R - G
How the Dividend Discount Model is Useful
The dividend discount model is a quick and dirty method for decisions in buying and selling securities. If the 'Price of Stock' from the model is less than the actual stock price, than the stock holders should try to sell their stock or on the other hand, potential investors should not buy the stock. If the 'Price of Stock' from the model is more than the actual stock price, then the potential buyers should buy the stock because it is undervalued, or stock holders may decide to keep the stock.
Although this model is simple, it is a quick way to evaluate stocks and is readily available with only a few necessary variables.
References
Luebke, Cathy. US Airways Shares Fall as JPMorgan Downgrades Airline Stocks. Phoenix Business Journal. 12 March 2008. Retrieved March 12, 2008 from http://www.bizjournals.com/phoenix/stories/2008/03/10/daily27.html?jst=b_ln_hl
The article, US Airways Shares Fall as JPMorgan Downgrades Airline Stocks, discusses the decrease in airline stock prices such as Tempe and other large airlines. Due to rising fuel prices and a weakening economy, Standard & Poor's Ratings Services plan to review the top ten US airline companies. For example, "US Airways stock closed at $9.98 per share Tuesday and dipped to $8.87 Wednesday before starting a rebound to end the day at $9.44 (Luebke 2007)."
Who is Affected?
Stock holders with risky stock such as the airline industry need to know when to buy in the market and when to sell their stock. In this situation, the main decision makers in this situation are stock holders such as the corporation and individuals.
What Model Should be Used?
A simple financial model known as the Dividend Discount Model (DDM). DDM tells you the value of equity, which is stock. Three variables are needed to determine the current value/price of stock. First, the dividend amounts are needed for a base period and for the following period after that. Second, the percentage of total expected return by investors (current income + price change), which is defined as variable R. Third, the annual growth rate from the base period and the next period is needed, which is defined as variable G. To find the stock's price, divide the next period's dividend amount by R minus G as so:
Price of Stock = Dividend of Next Period
__________________
R - G
How the Dividend Discount Model is Useful
The dividend discount model is a quick and dirty method for decisions in buying and selling securities. If the 'Price of Stock' from the model is less than the actual stock price, than the stock holders should try to sell their stock or on the other hand, potential investors should not buy the stock. If the 'Price of Stock' from the model is more than the actual stock price, then the potential buyers should buy the stock because it is undervalued, or stock holders may decide to keep the stock.
Although this model is simple, it is a quick way to evaluate stocks and is readily available with only a few necessary variables.
References
Luebke, Cathy. US Airways Shares Fall as JPMorgan Downgrades Airline Stocks. Phoenix Business Journal. 12 March 2008. Retrieved March 12, 2008 from http://www.bizjournals.com/phoenix/stories/2008/03/10/daily27.html?jst=b_ln_hl
Subscribe to:
Posts (Atom)