ANDERS P. BECKLUND
Address: *** **** ***** **., *****, GA 30809
Phone: 706-***-****
E-mail: ***************@*****.***
OBJECTIVE: To obtain a position in a challenging work environment that
emphasizes data analysis, problem solving, and engineering
experience to optimize work processes and reduce costs
EXPERIENCE: 2014-Present The Nutrasweet Company Augusta, GA
Front End Area Leader
Supervise operation of the Synthesis area of the plant
Manage all facets of the Front End operation from solving
daily problems to identifying efficiency improvements to
prioritizing maintenance activities
Lead the Yield Team in identifying yield improvement
opportunities for the entire plant which resulted in an annual
savings of $300K/yr
Provide leadership and direction for operations personnel
Perform monthly accounting of raw material inventories,
monitor the plant VOC system, and oversee Tank Farm operations
2000-2010 DSM Chemicals Augusta, GA
Process Engineer
Apply statistics to analyze process changes and develop
control charts
Analyze business costs to help improve production efficiency
Design projects for Evergreen and DSM plants to meet
production needs
Identify improvement opportunities and develop cost effective
solutions
1995-2000 ExxonMobil Chemical Baton Rouge, LA
Contact Engineer
Provide technical support for Production to rectify daily
operational problems
Create programs and spreadsheets to monitor raw material
utilization and facilitate resolution of atypical performance
Serve as environmental coordinator for the business group
EDUCATION: 1989-1993 Clemson University Clemson, SC
Bachelor of Science, Chemical Engineering - GPA: 3.8
1993-1994 Clemson University Clemson, SC
Post-graduate Study, Chemical Engineering - GPA: 3.9
OTHER: Black Belt 6-Sigma Statistical Analysis Training
Proficient in MS Excel, MS Word, MS Access, MS PowerPoint, and
SAP
Augusta Arsenal Soccer Club, Head Coach (2008-2013)
Excellent Technical Writing and Communication Skills
Intermediate French
ACCOMPLISHMENTS: Created Comprehensive Business Cost Model
A comprehensive financial analysis of the business was
performed to create a modeling tool for determining the
unit cost of production. The Excel model included both
fixed and variable cost data and enabled comparison of
production costs from different plants to establish best
practices. The Excel model and findings were presented to
company executives to help make major decisions regarding
the direction of the business and where to invest our
operating budget.
Led Team to Determine the Process Operating Window
In order to optimize efficiency, a process operating window
was created for the manufacturing unit. A cross-functional
team was formed to determine critical operating parameters
and their respective limits. Statistical analysis using
the 6-sigma methodology was applied to these variables to
establish operating and control limits. A procedure then
was written, implemented, and communicated to production
personnel to help maintain operational stability.
Automated Raw Material Accounting
Programs were created using Excel and other site specific
software to monitor the loss of various raw materials. The
programs facilitated raw material accounting and used
statistical analysis to determine when and where
non-routine losses were occurring. The program also helped
identify under-performing heat exchangers based on a
reduction in heat transfer coefficient.
Identified and Corrected Supply Pump Limitation
Historical plant data was collected and analyzed. The data
analysis revealed that a supply pump was undersized for
current production rates and was limiting production. A
new pump was sized and installed which eliminated the
bottleneck and resulted in significantly increased
production rates.
Developed a Mathematical Model to Predict Impurity
Concentrations
Numerical integration was utilized to estimate residence
time for multiple plug flow and well-mixed systems in
series. The model helped accurately estimate impurity
levels with improved response time. An analysis of
variance for the test results confirmed that a
statistically significant improvement had been made.
Downtime when switching product lines was minimized which,
in turn, increased overall production.