Proceedingsedge.rit.edu/edge/P11713/public/P11713 Technical Paper.docx · Web viewEnergy efficiency...

Multi-Disciplinary Senior Design Kate Gleason College of Engineering

Rochester Institute of TechnologyRochester, New York 14623

Project Number: 11713

Wegmans Bakery Energy AuditElizabeth Day, Industrial & Systems Engineering Carl Shatraw, Industrial & Systems Engineering

Chuck Nwapa, Mechanical Engineering Lucas Zamoyski, Mechanical Engineering

ABSTRACT

Energy efficiency and conservation have become important concerns among various industries. This report includes information on the energy reduction strategy designed for the bakery at Wegmans Food Markets, Inc. The strategy describes action items and suggests methods for future work and improvements as well as identifies energy savings opportunities and respective economic implications, if applicable. Recommendations for managing energy efficiency and conserving energy were made based on the bakeshop’s historical energy data, on-site discussions and observations as well as general research.

BACKGROUND

Wegmans Food Markets, Inc. is a family-owned U.S. grocery chain based in Rochester, New York. The chain consists of 80 stores spread across New York, Pennsylvania, New Jersey, Virginia, Maryland, and Massachusetts. Wegmans has appeared on Fortune’s annual “100 Best Companies to Work For” list since its launch in 1998 and has ranked amongst the top 10 for eight consecutive years.(1) The 235, 000 square-foot bakeshop produces Wegmans-brand baked goods that are distributed to all stores. The bakeshop includes production, warehouse and shipping areas and is operating approximately 260 days per year.

METHODOLOGY

The main objective was to determine an energy use benchmark by thinking about how to approach studying current state, identify opportunities for improvement, and prioritize said opportunities. The project was broken down at the systems level to energy types (water, air, gas and electric) and categories of improvement (process and engineering). Ideally, to deliver applicable results and recommendations, analysis and research of past energy consumption patterns need to be gathered to develop a

baseline for improvement. However, it was readily discovered the intended methodology would not prove to be successful due to the early age of the energy efficiency initiative in the bakeshop.

It was discovered in the beginning stages of the project that in order to reach the overall objective of an energy benchmark, a commitment has to be made at all levels of the facility. Energy Star(2) has developed guidelines to promote energy management and assist organizations in improving its energy and financial performance while aiming to become an environmental leader. Figure (1) displays the flowchart associated to the seven steps that need to be taken in order to gain control over energy efficiency. For the intentions of this project, the flowchart was adapted with the first four steps being the main focus. The adapted version is referred to as an “Energy Strategy for the Future” as shown in Figure (2). As commitment to energy efficiency continually grows and improves, these four steps provide a concrete foundation.

To expand on the flowchart, a matrix describing each step in detail with current state, future state and next steps was developed (reference Appendix A for complete matrix). Current states were defined by on-site observations and conversations with those involved in the step. Step 1, commit to continuous improvement, includes site energy leader, site energy champion, site energy team, site energy policy, accountability, and participation levels. Despite the size or purpose of organization, the common element of successful energy management is commitment. Organizations make a commitment to allocate staff and funding to achieve continuous improvement. Step 2, assess performance and opportunity, encompasses track and analyze data, documentation, benchmarking, technical assessments as well as best practices. By understanding current and past energy opportunities, it becomes easier to advance energy performance and improve financially.

Assessing performance is a process aimed to analyze patterns of energy use for the bakery and assists in establishing a baseline for measuring future results of efficiency efforts. Step 3, set performance

Project 11713Copyright © 2011 Rochester Institute of Technology

Source: Energy

Star

Proceedings of the Multi-Disciplinary Senior Design Conference

goals, consists of goals, career development and site energy incentives. Well-defined intentions guide everyday decision-making and provide the basis for tracking and measuring progress. Communicating and posting goals can encourage employees to support and continue to commit to energy management endeavors. Step 4, create action plan, incorporates the previous three steps in addition to improvement planning, rates and resources and site planning integration. Once the bakeshop has completed the first three steps successfully, a detailed action plan will ensure a systematic progression to implement energy performance measures. Unlike the energy policy that is part of step 1, the action plan is updated at regular intervals to reflect recent achievements, alterations in performance, and changing priorities.

Figure (1) - Energy Star Structure (2)

Figure (2) - Energy Strategy for the Future

SITE PROFILING

This project started with a blank slate in terms of data. The team had to make a plan on what data was needed and if that data currently exists somewhere at Wegmans. Next, if it did not exist, could it be collected in the amount of time the team had for this project, or could it be recommended to be collected in the future. This process was one of constant discovery and exploration. The data was

obtained with help from many different departments and employees.

First, the team wanted to know the amount of money that Wegmans is spending on their utility bills including electric, gas, and water. These were obtained early in Senior Design I. Natural Gas use was heavier in the colder months while electric was high all year round. Water usage was very small financially compared to gas and electric.

After touring the facility multiple times and looking at the floor plan that the group attained, the group got a feeling of what product lines were running at the bakery. Next, the production data by product line was attained. Then the average run time of each product line was attained. Next, the units of measure were attained of the product lines. The production rate was then calculated for each product line.

To pinpoint the biggest energy users, the team explored one-line electrical diagrams of the bakery and the inputs that fed the different circuits. The idea of this was to use the basic formula for calculating kW-h use of machines to see what would be the biggest user of electricity. While analyzing these drawings, which were new to the team made up of industrial and mechanical engineers, the team discovered a Wegmans intern had undertook a similar venture while working for Wegmans. The team looked this data over, which specifically named the specifications of many different breakers in the bakeshop. The team concluded that this data was too broad for what it was intended for. A much smaller machine by machine outlook had to be undertaken.

This led to discovering a listing of most production equipment at the bakery that was created in 2003. This list was not well organized and was very long. The team walked through the plant trying to identify the biggest electric users from the list. This led us to explore a lot of high-impact motors that ran for great lengths of the day. There is a gas meter on the biggest oven in the bakery, called the tunnel oven. This was manually read daily for 2 months to generalize gas usage for the ovens in the facility.

The group aimed to identify some areas of the bakery that provided opportunities for improvement in thermal leaks. A thermal camera was obtained and photos were taken of the bakeshop with the help of the Center for Imaging Science at RIT. The main areas targeted were doors from cold areas to warm areas.

DATA ANALYSIS

Heat Loss from Unused Pipe LegsBy analyzing heat loss from unused pipe legs,

the objective was to quantify the amount of energy lost due to convection from unused hot water pipes throughout the facility. Assumptions needed to be made in order to complete the analysis. They included

Copyright © 2008 Rochester Institute of Technology


radiation can be neglected due to low emissivity, steady state in the bakery, natural convection, constant properties of both air and water, constant air temperature due to large size of facility, constant water temperature due to constant use of hot water, ideal gas and neglected insulation for simplification and lack of knowledge of material used.

A visit was made to Wegmans Bakery to obtain data, shown in Figure (3) related to the hot water pipe system. Temperatures were taken on the pipe surface near spouts and just under the insulation. Ambient air temperatures were also collected. A measurement of the pipe diameter was also recorded for the analysis.

Ambient Temperature (°F) 80Average Surface Temperature of pipe (°F) 125Pipe diameter (in) 0.875

Figure (3) - Hot Water Pipe System Data

Total energy lost was calculated using Equation (1). Where Rtot is the total thermal resistance of the system (convection of air), and T inf is the temperature of the air in the bakery.

q=( Twater - Tinf )R tot

Equation (1) - Total Energy Lost

The resistance of the air was calculated by first finding the Nusselt number(4) from Equation (2). The Nusselt number is representative of the temperature gradient at the surface and provides a measure of the convection heat transfer occurring at the surface.

Nu D=[0.60+[0.387 RaD1/6

(1+ 0.559Pr

1/6)8/27 ] ]

2

Equation (2) - Nusselt Number

The mean temperature is depicted in Equation (3).

Tm =Ts + Tinf

2Equation (3) - Mean Temperature

The volumetric thermal expansion coefficient provides a measure of the amount by which the density changes in response to a change in temperature at a constant pressure. (4) Assuming an ideal gas the equation reduces to Equation (4).

β= 1Tm

Equation (4) - Volumetric Thermal Expansion Coefficient

Transition in free convection depends on the relative magnitude of the buoyancy and viscous forces in the fluid. These are correlated in terms of the Rayleigh number(4) as calculated using Equation (5).

R ad = g (β ) (T s- T inf ) (D3 )v(α)

Equation (5) - Rayleigh Number

From the Nusselt number the coefficient of convection can be calculated by using Equation (6).

h =( Nud ) (k )D

Equation (6) - Convection Coefficient

Using Equation (7) finds the convective resistance of the pipe.

R = 1

(2 ) (π )(D2 )(h)

Equation (7) - Convection Resistance of Pipe Surface

Entering this value into Equation (1) returns the total heat loss per unit length of pipe.

Using the collected data and the presented equations the total amount of energy lost per unit length of pipe is approximately four Watts or 100 Watts per day; this is equivalent to leaving a 100 Watt incandescent bulb on for one hour. However, based on the assumptions made the amount of heat loss will be significantly lower when the effects of pipe insulation are included in the model. Based on the results of this investigation, it is not a financially significant opportunity of improvement.

Thermal ImagesA thermal camera was used to target leaks in

seals around cold storage doors, windows, and other access points (reference Appendix D for a gallery of sample images). To quantify these leaks a heat transfer model was generated. Several assumptions were made to generalize the analysis, such as neglecting radiation, maintaining a steady state, natural convection, constant properties of air, constant air temperature due to large size of facility and large coolers, and ideal gas.

The images were used to establish a cooling area of a constant low temperature. It was then



assumed that this area would be heated by natural convection to the ambient bakery temperature. Transition in free convection depends on the relative magnitude of the buoyancy and viscous forces in the fluid. These are correlated in terms of the Rayleigh number(4) as calculated using Equation (8).

R ad = g (β) (T s- T inf ) (L3 )v (α )

Equation (8) - Rayleigh Number

The resistance of the air was calculated by first finding the Nusselt number(4) from Equation (29). The Nusselt number is representative of the temperature gradient at the surface and provides a measure of the convection heat transfer occurring at the surface.

NuD=[0.825+[0.387 RaD1/6

(1+ 0.492Pr

9/16)8/27 ]]

2

Equation (9) - Nusselt Number

From the Nusselt number the coefficient of convection can be calculated by using Equation (10).

h =( Nud ) (k )D

Equation (10) - Convection Coefficient

Using the coefficient of convection the heat loss can be calculated using Equation (11), Newton’s Law of Cooling(4).

q = hA (Tinf -Ts )Equation (11) - Newton's Law of Cooling

Using the largest temperature gradient obtained from the thermal images and the largest leak area the maximum amount of energy loss was obtained using this model. Approximately 22.7 Watts-hour is lost through this large leak. This is a relatively small amount of energy, about 200 Kilowatts per year or leaving a 100W bulb on for 11 weeks. However, if every leak is losing the same amount of energy those numbers are closer to 2,000 Kilowatts per year.

ConveyorsThere are a multitude of conveyors that

zigzag throughout the bakery; with each leg running on a separate motor these systems can waste energy when left running. When left running with no product on the conveyors the motor is considered unloaded. In an unloaded state a motor’s efficiency drops

significantly, for instance the motors most commonly found on the bake shop conveyors have an efficiency of approximately 80% when fully loaded, however at a quarter of the load the efficiency drops to around 61%. For these calculations a quarter of the load was assumed since it is expected that the conveyor belt alone applies some load to the motor. Figure (4) depicts the data collected and utilized in Equation (12) to calculate the cost of running a conveyor for a given time, t.

Horse Power hp 0.13Power Factor (%) pf 0.416

Efficiency (%)Eff 0.61

Hours run t 1Energy Rate($/kW) r 0.17

Figure (4) – Conveyor Data

hp*746Eff*pf

(t)(r) =cost of energy

Equation (12) - Cost of Energy for Running Conveyor

The results of these calculations show a cost of $0.06 per hour that a conveyor is left running unused. Although this seems like an insignificant number it can add up quickly. If one can imagine a line containing seven conveyor motors left on from the last shift on Saturday afternoon till the next shift comes in on Sunday, approximately 12 hours. Leaving this line on during this time would cost $5.50 for one day or $284 over the year if the conveyor continues to be left on.

Waste Heat RecoveryThe first step in the heat recovery road map

of the bakery was to identify all possible avenues in the bakery where there was an opportunity for recovering waste heat. The ovens quickly became the primary focus because of their large production load. Due to available data and the ease of collecting information, the tunnel oven and cookie oven were selected as baselines to calculate wasted heat and potential energy savings. Operating schedule of each oven (hours per year) was determined in order to adequately quantify dollar amount of savings from the heat recovered. The flow rates and temperature values were all determined for the calculation of waste heat recovered. After the sensible heat recovered was determined, it was then converted to dollar savings and used with the cost of installation to determine the economic justification of heat recovered.

In order to accurately determine the correct amount of heat recovered, different pieces of information were collected from the bakeshop over a



time period of 15 weeks. Utility bills of the bakeshop were obtained over a period of two years. These bills consisted of water, electricity and natural gas bills. This information was collected to give a base point to calculate the cost per square foot that assisted in determining savings after waste heat has been recovered. All additional information was collected through on-site observations.

The operating temperature of the ovens was collected because they were an important piece of information used in determining the waste heat recovered from the ovens. The operating temperatures of the ovens, number of exhaust outlets on the roof, and the exhaust temperatures were determined during a walk-through of the bakeshop. Entrance and exit temperatures were obtained during an on-site walkthrough by using a thermocouple. The flow rate of the air entering and leaving the oven was very important in calculating the waste heat recovered from the oven. Flow rates of the ovens were determined via the exhaust fans specifications. All data collected and obtained are depicted in Appendix B, which is a subset of a larger database that was provided to the customer separately.

To determine the waste heat that could be recovered from the ovens, a sensible heat recovery analysis was done on the tunnel oven and the cookie oven based on a standard cycle of heat recovery.(6) This cycle can be used on systems where exhaust air temperatures do not exceed 300 °F. Again, analysis was based on the tunnel oven and cookie oven because they are the two highest-capacity ovens in the bakeshop and had the largest quantity of accurate information available.

The actual cubic feet per minute (ACFM) flow rate of the exhaust was obtained from the oven exhaust fan specs. The Tunnel oven current utilizes a Siemens New York Blower Motor with a COMPACT GI Fan(5).

The exhaust flow rate, shown in Equation (13) (6) is in terms of standard cubic feet per minute (SCFM) and is the conversion of the ACFM based on the altitude density ratio. This would be used in determining the sensible heat that can be recovered from the oven. Altitude density ratio is based on the temperature of exhaust air.

SCFM=Altitude Density Ratio(ACFM) Equation (13) – Exhaust Flow Rate

The initial temperature difference (ITD), depicted in Equation (14) (6), is the entering exhaust air temperature minus the entering supply air temperature.

ITD=Exhaust air temperature-Supply air temperature (Ambient air temp of bakeshop )

Equation (14) – Initial Temperature Difference

The supply side temperature difference is the temperature difference utilized when calculating the sensible heat recovery. It is calculated by multiplying the ITD described above with the recovery factor, heat exchanger efficiency, as shown in Equation (15) (6).

Supply Side Temperature=(ITD)(Recovery Factor)Equation (15) – Supply Side Temperature Difference

Sensible heat recovered is the amount of sensible (dry-bulb) heat that can be supplied from the exhaust air to the supply air entering the building. The amount of heat transferred is described in Equation (16) (7) where 1.08 is the constant for sensible heat equations and η is heat exchanger efficiency.

H= (Supply SCFM ) (Supply side Temperature difference )(1.08)(η) Equation (16) – Amount of Heat Transferred

In order to translate the amount of waste heat recovered from the ovens into dollar amounts the cost of energy per 1,000 SCFM was determined and in turn used to calculate the amount of dollars that would be saved from the waste heat recovered. Dollar savings was calculated using the amount of heat to be recovered, number of hours the bakeshop runs per year along with the cost of energy which was found to be $12.96 per 1,000 SCFM. (7)

Based on the waste heat energy recovered from the ovens it was determined that there was a considerable amount of savings available from the tunnel and cookie ovens respectively. Installation and equipment costs of the run around heat coil exchanger and ducting fan would be approximately $26,000 for the tunnel oven. (6) Savings and payback on investment varied depending on the amount of hours each oven ran per year. This is shown in tabular form in Appendix A. As shown above, the bakeshop has room for large savings to be made especially on the ovens. Effective implementation would lead to realization of savings.

Start-Up AnalysisIn order to develop a model for start-up costs

and costs of running ovens in the bakeshop per hour, the tunnel oven was analyzed as a baseline. Cost per hour was calculated for the tunnel oven to start it up and heat it up to a temperature of 388 °F. Analysis was also done to determine the cost of maintaining the oven at an idle temperature of 196 °F.

The therms per hour value was collected directly from the tunnel oven meter readings and was converted to cost per therm value by multiplying by a factor of $0.84/therm. This value represented the cost



of running the oven per hour during an idling period at Wegmans. The oven was assumed to be running at normal operating temperature of 388 °F. In order to determine the cost per hour in dollar terms for the oven when running at a mid-temperature of 212 °F the therm per hour value was converted to kW-h and a new temperature difference was applied reflecting the new midpoint temperature of 212 °F. This value was then converted back to a dollar per hour value using a conversion factor of $0.84/therm.

After obtaining the total thermal resistivity of the tunnel oven, the energy required to keep the oven at a particular temperature can be solved for using Equation (17).

Q idle =∆T/ R totalEquation (17) – Energy Required

To compare the costs of running an oven at a lower temperature versus turning it off when not in use, the cost of heating the oven to full temperature must first be obtained. The general equation for heating a given mass to a certain temperature is noted in Equation (18).

qstartup =mCp (∆T)Equation (18) – Heating a Given Mass

Where m is the mass being heated, Cp is the specific heat capacity of the mass and ∆ T is the change in temperature. For case one, heating from half temperature to cooking temperature is given by Equation (19).

∆T=(388°F-194°F) Equation (19) – Change in Temperature

For case two, heating from ambient to cooking temperature:

∆T=(388°F-80°F)Equation (20) – Ambient to Cooking Temperature

Unfortunately, measuring the mass and finding the specific heat capacity of the oven is not a trivial matter. The mass will include everything from the belt to the insulation and the air being heated inside the oven each with different specific heats. If these numbers were known the amount of energy required to bring the oven up to temperature could be obtained for both cases. With this number the time to heat the oven could also be obtained using Equation (21) below:

Energy required for temperature changeEnergy rate of oven

Equation (21) – Time of Oven Heat-up

For example if the energy required was 1, 000 kW and the oven supplies 2,000 kW-h it would take 30 minutes to heat up. The time to heat can be used to minimize wait times for oven reheat. This time is also need to calculate the cost differential between the two cases. For case one the total cost will be:

Total Cost= (Idle time×Q idle ×qstartup ) ×Cost of energyEquation (22) – Total Cost Case 1

For case two the total cost will be:

Total Cost=qstartup×Cost of energyEquation (23) – Total Cost Case 2

From the above equations one can see that the optimal case will be based on the amount of idle time between shutdown and startup of the oven. The longer this time the cheaper it will be to turn the oven off while shorter times will make idling the oven at higher temperatures more cost and time efficient.

It was determined that when the oven is running at 388 °F it costs $8.13 an hour to run while it costs approximately $3.40 an hour to run when it is running at 212 °F while idle. All results are depicted in Figure (5).

Temp of 388 °F kW-h (388°F ) 284.89therms/hour 9.69 Temp at 212 °F kW-h (212 °F) 122.00therms/hour 4.15Figure (5) – Start-Up Analysis

RECOMMENDATIONS

5.1 Policy Improvements

Motor InvestigationBased on the research done inside the facility

on the motors in Peerless mixers, they have been targeted as high energy users. This conclusion is based on the high run times for the lines they are associated with and the high energy consumption of the large mixer motors. Since the motors are fairly new and running in proper order it is most beneficial to keep the current motors. However, when repairs are needed or new mixers/motors are to be purchased the flowchart(3) designed (reference Appendix C) should



be followed to ensure the best energy and financial benefits.

5.2 Process ImprovementsThere is a large portion of all energy use that

is directly controllable and dependent on people’s behavior. This is what the team tried to target in this group of projects. First, the thermal leak data was explored. Though the savings potential was not substantial, it was concluded that it would be beneficial to have an employee complete a thermal leak checklist quarterly to ensure the door and windows were properly closed as they should be. The current state is that the plastic windows on sliding doors are unattached at some corners and the sliding doors to the cooler rooms do not fully close.

Next, the team looked at the charging habits of Wegmans for their forklifts and powered material handling vehicles. There is a 42% savings in delivery charges for non-peak energy delivery. Therefore it would be beneficial to charge the vehicles after 9pm and on weekends instead of during peak hours. Assuming a forklift is charged 260 times a year for 8 hours each time, if all of these charges were during peak times, the company would save about $1400 per year by charging during non-peak hours. This could be done for about 17 vehicles. It is difficult to gauge the charging habits now; they are charged on demand. Therefore, potential savings from making a disciplined charging schedule range from $7,000 to $23,000. This would include sharing vehicles to level the demand between departments. Now, each department has their own vehicle, some used all day, some used very rarely.

Next, water management was explored. The financial impact was very minimal of reducing water use. Also, most cleaning procedures already existed. A new cleaning machine for pans is currently being purchased to reduce water usage by recycling water. However, it would be beneficial to reduce the amount of solid waste that goes down the drain to reduce the amount of treatment the water needs to receive.

The current electric utility billing structure that Wegmans has is based on the current running times and electric usage profile. If some of this demand can be leveled and moved back to “off-peak” demand times, 9 p.m. to 9 a.m. and weekends, the base rate can be renegotiated and peak demand charges can be greatly reduced. Electric delivery rates are 42% lower in off-peak hours, which provide a substantial opportunity for monetary savings. As an increased amount of production and non-production operations are shifted to off-peak hours, the rates should be renegotiated.5.3 Engineering Improvements

Another avenue of the bakeshop where potential waste heat savings were present was the

boiler room. However no waste energy analysis was done on the boiler room because of the time limitation of this project. Other areas considered were waste heat energy from pipes and water. However due to the time constraint factor of this project focus was placed on the ovens.

CONCLUSION

This report outlines the comprehensive actions taken to generate widespread recommendations aimed at improving energy efficiency in the bakeshop. After these recommendations are discussed and potentially implemented, energy targets will require monitored usage. An ongoing energy management program as described in the methodology section and Appendix A will also be imperative towards building a solid energy strategy for the future. These recommendations are not guaranteed to reduce the cost of future energy use, however commitment at all levels of the operation, proper implementation and standardizing operating procedures should reduce net energy consumption overall.

REFERENCES

[1] www.wegmans.com [2] http://www.energystar.gov/index.cfm?c=guidelines.guidelines _index[3] www.energysc.org/downloadables/high_efficiency_motors.pdf[4] Incropera, DeWitt, Bergman, & Lavine. (2007). Fundamentals of Heat and Mass Transfer[5] http://www.nyb.com/? gclid=CKXzh7v6v6gCFUJ-5QodfFt4qQ[6] Run Around Heat Recovery 2007 pg (1-45) K70-RA-PDS-11www.keepriterefrigeration.com[7] Engineering Toolbox 2002 122:611-619. pg (1) www.engineeringtoolbox.com

ACKNOWLEDGEMENTS

Faculty Guide: John Kaemmerlen, Industrial & Systems EngineeringFaculty Consultants: Dr. Brian Thorn, Industrial & Systems Engineering Dr. Rob Stevens, Mechanical EngineeringJohn Wellin, Mechanical EngineeringThermal Camera: Joe Pow and Stefano Prezioso, Center for Imaging ScienceCustomer: Wegmans Food Markets, Inc.Customer Guides: Scott Young, Director of Manufacturing Engineering & Bakeshop ServicesEric MacCormack, Manufacturing Engineer



APPEDICIES

Appendix A – Energy Strategy for the Future MatrixAdapted from Energy Star's "Facility Energy Assessment Matrix"http://www.energystar.gov/index.cfm?c=guidelines.guidelines_index

Assessment Date: February 4, 2011

Current Future Next Steps

Site Energy Leader Assigned responsibilities but not empowered Energy Leader established and supported Establish an Energy Leader, such as Team Leader or Line Manager and ensure he/she is supported of site manager

Site Energy Champion None identifiedSenior manager works to support energy program & promotes energy efficiency; those responsible for finances listed

Senior manager is aware and supportive of energy program & promotes energy efficiency; identify who controls finances

Site Energy Team Informal organization with occassional activity Team meets on a regular basis to guide site energy program Create meeting schedule for team should meet to ensure continuous improvement of site energy program

Site Energy Policy No energy policy Implemented organizational policy that is supported at all levels & continue adapting on road map

Create written plan & begin implementation of an organizational policy (roadmap) for energy efficiency that can be supported at all levels

Accountability Estimates used for allocating energy budgets

Monitor and track data from meters on key users, maximum energy required is known & goal set for __% reduction each year; each entity is responsible for their own energy efficiency

Continue to place meters on key users; research possibility of implementation "cap and trade" system to improve energy efficiency

Participation Levels Some participation, sharing, mentoring, & professional memberships; Annual reporting of performance

Participatory in energy organizations & best practices are shared; Reporting is regular (or continually increasing) to identify areas for improvement

Participate in energy organizations & share best practices; Increase reporting

Track and Analyze Data Limited metering & tracking; No demand analysisMeter, track, analyze, & report key loads are appropriately documented; Adjustments made for real-time demand, & peak times analyzed

Begin to meter, track, analyze data in order to identify key loads; Adjust real-time demand, & analyze peak times

Documentation Limited amount of documentation & records; High-level review of equipment specifications

New machines & processes are documented (Standard Operating Procedures)

Update all machine information & document best practices (Standard Operating Procedures)

Benchmarking Energy performance of systems & facilites not benchmarked

Key systems & data managed in a portfolio with owner listed

Develop portfolio that contains key systems & data (with owner)

Technical Assessments Limited review by vendors, location & corporate energy managers

Energy committee performs extensive energy reviews at regular intervals (~5 years, possibly with assistance from external professionals)

Set schedule for energy committee to perform extensive energy reviews at regular intervals

Best Practices None identified SOPs are monitored & updated as needed; Active participant at energy conferences Maintain, update, share & implement SOPs

Goals/Potential Loosely defined objectives; Limited awareness of energy goals by others outside of energy committee

Use road map; Follow goals identified & update as necessary

Create road map with clearly stated goals (roll up to department/site/corporation)

Career Development No career development or opportunities Those identified as energy professionals have clearly stated career paths & are continuously encouragement Identify who is accountable for what information (owners)

Energy Team Incentives No ties between energy efficiency improvement & incentives

Provide encouragement for energy efficiency to employees through employee incentives

Provide encouragement for energy efficiency to employees through employee incentives

Improvement Planning Upgrades implemented sporadically; Some compliance with organizational goals and standards

Full compliance with organizational energy efficiency design guidelines and goals

Document improvement methodology (to include upgrade plans that reflect assessments)

Roles and Resources Addressed on ad hoc basis only Internal & external roles identified; Budgets used to monitor funding

Internal & external roles need to be identified (organizational structure); Set baseline for funding (budgets)

Site Planning Integration Decisions impacting energy considered on first-cost basis only

All large projects include energy analysis with return-on-investment calculations & lifecycle assessment(s)

Develop policy for all large projects that includes energy analysis with return-on-investment calculations & lifecycle assessment(s)

STEP 1: Commit to Continuous Improvement

STEP 2: Assess Performance and Opportunity

STEP 3: Set Performance Goals

STEP 4: Create Action Plan

Appendix B – Waste Heat Recovery DataTunnel oven heat recoveryCFM exhaust 2500SCFM 1875Altitude density ratio 0.75Exhaust air temp 290Operating temperature (F) 388Initial temperature difference (ITD) 308Temperature (F) 80Supply side change in temperature 200.2Run around coil heat exchanger H (heat transferred btu/hour) 265000Q (Airflow/CFM) 1875t1, air temperature of the exhaust air before unit (oF) 290

t2, air temperature of outside air after unit (F) 80η, heat-recover efficiency 65%

Table (A) - Tunnel Oven Sensible Heat RecoveryCookie oven heat recovery CFM exhaust 2200SCFM 1650Altitude density ratio 0.75Exhaust air temp 200Operating temperature (F) 370Initial temperature difference (ITD) 290Temperature (F) 80Supply side change in temperature 188.5



Run around coil heat exchanger H (Heat Transferred Btu/h) 219000Q (Airflow/CFM) 1650t1, air temperature of the exhaust air before (oF) 200

t2, air temperature of outside air after (F) 80η, heat-recover efficiency 65%Table (B) - Cookie Oven Sensible Heat Recovery

Tunnel Oven Cookie OvenEnergy Savings Savings Payback Savings PaybackCost of Energy ($/1000 SCFM) 1 Shift $8,000 38 to 40 months $9,000 34 to 36 months2 Shifts $15,000 20 to 22 months $18,000 17 to 19 months3 Shifts $22,000 13 to 15 months $27,000 10 to 12 months

Table (C) - Tunnel Oven & Cookie Oven Savings

OvenOperating Temp (oF) CFM

# of Exhaust Outlets

Exhaust Temp 1 (oF)

Exhaust Temp 2 (oF)

Exhaust Temp 3 (oF)

Entrance Temp (oF)

Exit Temp (oF)

Bread Oven 400 - 2 185 - - 104 -Roll Oven 425 - 3 190 195 193 - 87Tunnel Oven 380 2500 3 290 230 230 141 -Cookie Oven 1 365 2200 2 200 168 - - -Cookie Oven 2 433 3 322 - - - 99Parbake Oven - - 3 265 255 286 100 112

Table (D) – Oven Data Collection

Appendix C – Motor Efficiency

Appendix D – Thermal Images



Image (A) – Top of Tunnel Oven Image (B) – Blast Freezer Door Image (C) – Maintenance Door Bottom


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