Email RIS file
Bookmark
Report an Issue

Energy-aware Models for Warehousing Operations

Author
Anand, Vidyuth
Published
[University Park, Pennsylvania] : Pennsylvania State University, 2014.
Physical Description
1 electronic document
Additional Creators
Prabhu, Vittal
Access Online

Availability

I Want It
I Want It

Finding items...

Graduate Program
Restrictions on Access
Open Access.
Summary
There is a growing need in industries around the world to become more sustainable and reduce consumption of energy. Due to the rapid increase in demand of goods, there has been a rise in demand of logistics and operational services. This necessitates the need for a large number of warehouses and distribution centers to satisfy the demand. Industries across the country have given this a fair amount of consideration, as the amount of money invested in business logistics in the United States in 2012 was $1.33 trillion, at 8.5% of the GDP. Being a key player in the market, it is imperative that warehouses follow the same sustainable development model practiced in other industries. The U.S. Census Bureau reported approximately 11,000 warehouse and storage facilities operating in the country in 2008 with employment of close to 600,000 workers who earned annual wages of nearly $21 billion. Warehouses account for 8% of the total energy consumption of commercial buildings across the nation. Despite a higher level of warehouse automation in the market today, forklifts are still a critical component of warehousing activity, and contribute significantly to the consumption of energy in warehouses. The U.S. alone is responsible for shipping more than 100,000 units of forklifts around the world today, translated to more than $30 billion worth of forklifts being bought by warehousing companies. We serve to leverage the EC1 energy control policy model for manufacturing systems to forklift queueing models in warehouses as an effective energy metric. Specifically, warehouses are modeled as M/M/c queues of forklifts. The model is extended to general distribution queues and experimentation based on real-world data for different distributions is carried out to infer outcomes based on the model, following which a scope for future work is described.
Other Subject(s)
Dissertation Note
M.S. Pennsylvania State University 2014.
Reproduction Note
Library holds archival microfiches negative and service copy. 2 fiches. (Micrographics International, 2015)
Technical Details
The full text of the dissertation is available as an Adobe Acrobat .pdf file ; Adobe Acrobat Reader required to view the file.
View MARC record | catkey: 13592064