ANDERS P. BECKLUND

Address: *** **** ***** **., *****, GA 30809

Phone: 706-***-****

E-mail: acpb6f@r.postjobfree.com

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.

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