energy consumption assessment in a conventional foodservice system

ENERGY CONSUMPTION ASSESSMENT IN A CONVENTIONAL FOODSERVICE SYSTEM

MARTHA J. BARCLAY, Ph.D., R.D.' Assistant Professor

Department of Home Economics The University of Iowa Iowa City, Iowa 52242

and

MARY JO HITCHCOCK, Ph.D., R.D. Professor

Department of Nutrition and Food Science The University of Tennessee Knoxville, Tennessee 3 791 6

Received for Publication February 14, 1984

ABSTRACT

A schematic energy flow decision model was developed for a conventional foodservice system. Quantitative energy consumption data were obtained by metering the flow of natural gas, steam condensate, and electricity in 15 selected pieces of foodservice equipment along the continuum from receiving through service for 11 menu items. The mean energy consumption by equipment during the food product flow of each menu item ranged from 240 to 3,076 British thermal units per pound menu item.

INTRODUCTION

During the 1970s, financial expenditures for energy resources increased from 2 to approximately 19% of the total operating budget for many foodservice operations (National Restaurant Association, 1979). Because of this noticeable increase in cost for energy resources and the projections for even greater financial expenditures in the future, identifi-

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Journal of Foodservice Systems 3 (1984) 33-47. All rights reserved. Copyright 1984 by Food & Nutrition Press, Inc., Westport, Connecticut.

33

34 MARTHA J. BARCLAY AND MARY JO HITCHCOCK

cation of energy resource consumption is important to the administrative dietitian. Identifying and monitoring energy resource consumption is the first step toward minimizing financial expenditures for energy. Theoreti- cal studies have described potential energy usage (Dwyer et al. 1977; McProud 1977); however, in-house metering studies are necessary to describe actual energy consumption. Therefore, the purposes of this research were: (1) to develop a schematic energy-flow decision model; (2) to meter the energy resource consumption along the food-product flow continuum, and (3) to determine the quantity of energy resources consumed to produce one pound of a selected menu item. This information, in turn, should assist the administrative dietitian in making decisions concerning effective energy usage in a foodservice operation.

EXPERIMENTAL METHODS

Prior to the actual metering of energy usage, a pilot study was conducted at one of The University of Tennessee, Knoxville, foodservice facilities to investigate the food-product flow of menu items; to identify the equipment to be monitored including the type of meter hook-up required and associated variables; and the beginning/ending points of food processing. Since metering took place during the actual storage, preparation, and serving of menu items at this cafeteria, food products were selected from the cycle menus on the basis of equipment required for processing and frequency of service. Selected items were roast beef, meatloaf, fried chicken, baked ham, egg products, bacon, sausage, corn- on-the-cob, green peas, vegetable soup, and oatmeal. All of the menu items studied were prepared from ingredients purchased according to specifications developed by the University Food Services using standardized recipes. Identical quantities of each menu item were used for each replication. The as-purchased (AP) mass of each menu item prepared was selected for monitoring instead of the edible-portion (EP) mass. Observations made during the pilot study suggested that even though a constant amount of each unprocessed menu item was prepared according to a standardized recipe, the resultant EP mass varied. In addition, this investigation was conducted in an ongoing operation of meal service to the students which could not be disrupted. All menu items were prepared with only one type of hot food preparation equipment, except meatloaf, and it was prepared in both the gas forced-air convection oven and the gas rotary oven.

ENERGY CONSUMPTION ASSESSMENT 35

Food Product Flow

Each selected menu item was followed from the receipt of the ingredients through the service of the prepared menu item. A minimum of three replications was made of the food product flow and the monitoring of the quantitative energy consumption along the flow for each menu item. The foodservice areas included the receipt, storage, preparation, holding, and service areas (Table 1).

Equipment

Electric, natural gas, and steam using equipment was identified. The electric equipment included a grill, deep-fat fryer, steam table, warming oven, slicer, and compressors for three refrigerators, and two freezers. The natural-gas equipment was the convection oven and the rotary oven. The condensate flow of a jet steamer, a 20-gallon steam jacketed kettle, and a 60-gallon steam jacketed kettle was metered. The equipment was maintained routinely by the inhouse maintenance staff. This study did not include the metering of sanitation equipment, lights, or the heating, ventilation, and air-conditioning (HVAC) system.

Metering

Meters used to monitor electric equipment were model MT 145 kilowatt-hour meters. Only three electrical meters could be installed at one time because of possible interference with electrical service and safety precautions; therefore, meters were periodically rotated between equipment. Hook-ups were made by splicing meter lines with current lines between the wall receptable and the equipment or between the fuse box and the equipment. Model No. lA, Sprague Gas Meters were installed in the gas input line of the rotary and convection ovens; model 00-1 1, Niagara Nutating Disc Liquid Meters were installed in the condensate line of the steam equipment. A copper coil was submerged in an ice bath preceding the condensate meter to slow the expulsion of condensate from the jet steamer only. All installations were approved by the local util- ity company representative and the University maintenance staff representatives.

Quantitative energy consumption data were obtained for each piece of equipment during the processing of selected menu items. Quantitative

Tabl

e 1.

Foo

dser

vice

are

as,

sele

cted

equ

ipm

ent

and

asso

ciat

ed v

aria

bles

mon

itore

d

Ax

Equipment

Associated Variables

Receiving

Refrigerat

ors

Power

rating

and

stor

age

Freezer

Dimensions

Ambi

ent

temperature

Initial product

temperature

Bus i

nesslnon- bus iness hours

Thermostat setting

Quantity of p

roduct s

tored

Product

k tored

Duty

cyc

le

Preparation

Refrigerat

or

Power

rating

Freezer

Diminsions

Ambi

ent

temperature

Initial product

temp

erat

ure

Business/non-business

hour

s Pr

oduc

t ktored

Thermostat setting

Quan

tity

of product

stored

Duty c

ycle

Grill

Power

rating

Ther

most

at setting

Deep

-fat

fryer Dimensions

Duty

cyc

le

Rotary over

Product

Quantity. of product prepared

Convection ove

n Product

temperature

Equipment

activity

Slicer

Power

rating

Product

Prod

uct temperature

Quan

tity

of product

Steam jacketed Power rating

Kettles

Capacity

Jet

steame

rs

Product

Product

temerature

Quantity o

f product

Equipment

activity

Holdin!

and

Warming oven

Power

rating

Product

temp

erat

ure

Duty c

ycle

se

rvic

e Steam tabl

e Dimensions

Quantity of

product

Equipment

activity

Product

Number o

f we

lls

filled1

Percent

fill o

f ov

en2

it; > z U

X

lfor steam table

Zfor

warming oven


energy consumption data was obtained for the grill during approximately 12 h of processing of eggs; for the deep-fat fryer during approximately 6 h of the processing of fried chicken; for the rotary oven during approximately 12 h of processing of meatloaf and roast beef; for the convection oven during at least three processing trials of baked ham, meatloaf, bacon and sausage patties; for the slicer during the processing of roast beef and baked ham; for the steam jacketed kettles during at least five processing trials for each corn-on-the-cob, oatmeal, and vegetable soup; and for the jet steamers during at least seven processing trials for peas. Meter readings for the refrigerators and freezers were taken during both the business and nonbusiness hours for three consecutive days for each piece of equipment to reflect a typical situation. Meter readings were taken during and between meal service periods for the holding and service equipment for three consecutive days during business hours, again to reflect a typical situation in this facility.

Variables

Variables associated with menu items, equipment used, or processing activities that might influence the energy consumption were identified. These included the menu item, associated quantity as purchased (AP) and temperature, equipment power rating, dimensions of equipment, duty cycle of equipment, equipment activity (on/off/idle), thermostat setting, ambient temperature inside refrigerators and freezers, number of steam table wells, percent fill of warming oven, personnel preparing menu items, and the 24-hour clock time (Table 1).

Beginning and Ending Points

Energy consumption monitored within each area began with the physical entrance of the product into that foodservice area and ended when the menu item was transported out of the designated geographical location. The beginning point for monitoring hot-food preparation equipment began when the equipment was turned on for preparation of the menu item and ended when the equipment was turned off. In the refrigerators, freezers, warming ovens, electric steam table, and steam equipment, metering began when the product was placed in the equipment and ended when the menu item was removed.


Data Collection

Between July and December 1978, a minimum of three energy resource metering replications were made for each piece of equipment used during the preparation of the menu items. In this facility approximately 1,500 meals were served per day during the summer quarter and over 4,500 meals were served per day during the fall quarter. A 3-week cycle menu was used during the summer quarter and a 4-week cycle menu was used during the fall quarter. The amount of time each piece of equipment was monitored during each replication and in total varied depending on the equipment processing time required for each menu item. Data relevant to each of the variables were collected concurrently with the energy consumption metering of each piece of equipment.

Analysis

All energy consumption data were converted to equivalent British thermal units (Btus): 1 kilowatt hour of electricity= 3,412 Btu; 1 cubic foot natural gas = 1,000 Btu; and 1 pound steam condensate = 1 ,OOO Btu. Apportioned energy consumed by each piece of equipment for each pound of a menu item was determined by appropriate formula. As an example, the following formulae were used to calculate the apportioned energy requirement for the grill and deep-fat fryer:

(1)

(2)

total kilowatt-hours during preparation period total pounds menu item prepared

Nr. kilowatt-hour/pound =

(Nr. kilowatt-hours) x 3,412 Btu/kilowatt-hour (pound menu item)

Nr. Btdpound =

The energy consumed by the refrigerators and freezers was apportioned by dividing the mass of the products used for the menu items on a parti- cular day by the maximum cooling load allowed assuming 30 lb of product per cubic foot (Kotschevar and Terrell 1977) and then multiplying the result by the mean hourly energy use of the equipment and the dura- tion of the equipment use time.

This apportioned energy was subtotaled for each area to determine area requirements for each menu item. Finally, the total apportioned energy requirement was calculated by adding the subtotals. Coded data were analyzed by the statistical analysis system (SAS-76) programs (Barr et al. 1976). Statistical significance of the variables was determined by


regression analysis followed by a f-distribution test. For each piece of equipment except for the holding and service equipment and refrigerators and freezers, data from all of the replications for all of the products processed in that equipment were used in the determination of the statistical significance of any variable. For the refrigerators and freezers, data were compiled for three consecutive days for each of three refrigerators and two freezers. The data for all of the refrigerators and for both freezers were used for the regression analysis followed by the f-distribution test. For the holding and service equipment data were compiled during three business days and then used for the statistical analysis.

RESULTS AND DISCUSSION

A schematic energy flow decision model was developed from the food product flow data for the conventional foodservice system (Fig. 1). The model identified foodservice areas and associated equipment. Modified energy flow models were developed for selected menu items. In this descriptive study, these models were used to sequentially analyze and contrast energy consumption between products and between preparation methods for the same product.

Results from the analysis of energy consumption, along the food-product flow, indicated that the apportioned energy per pound of menu items ranged from 0 to 7 +. 1 Btu per pound in the receiving and storage areas (Table 2); from 36 to 1,547 Btu per pound in the preparation area; and from 171 to 1,526 Btu per pound in the holding and service areas. The total apportioned energy per pound consumed along the food product flow for each menu item ranged from 240 Btu per pound for vegetable soup to 3,076 Btu per pound for baked ham.

Results from a regression analysis followed by an f-distribution test for each piece of equipment indicated that some of the variables identified were associated with the quantity of energy consumed by that piece of equipment. For example, the thermostat setting of refrigerators and freezers, deep-fat fryers, rotary oven, and warming oven significantly influenced the quantity of energy resources required to process a menu item (Table 3) -the higher the setting the more energy resource required.

The mass of each menu item prepared also had a significant influence on the quantity of energy required by the deep-fat fryer and the convection oven; the greater the mass the less energy resource required per pound. For example, preparation of 25.3 lb of baked ham in a partially loaded convection oven required more energy per pound than when the convection oven was fully loaded as with meatloaf (see Table 2). Convec-


RECEIVING

1 I

I

I packaging portioning slicers

1 HOLDING I

I

I t

c SERVICE

FIG. 1. SCHEMATIC ENERGY FLOW DECISION MODEL

tion ovens appear to be one piece of equipment that requires a specific amount of heat to heat the oven cavity which would suggest that the quantity of energy required is stable, and that as the amount of product heat processed increases, the quantity of energy required for heat processing per pound decreases. The same appears to be true for the deep-fat fryer, except that when the deep-fat fryer basket is filled beyond its

Tab

le 2

. Su

mm

ary

of m

ean

ener

gy c

onsu

mpt

ion

alon

g fo

od p

rodu

ct f

low

in t

he c

onve

ntio

nal

food

ser

vice

sys

tem

for

sel

ecte

d m

enu

item

s

Tot

al

Poun

d R

ecei

vin

g an

d S

tora

ge

Hol

ding

and

Ser

vice

T

otal

Ene

rgy

Item

M

ass

Btu

llb

. B

tull

b.

Btu

llb

. M

enu

(A.P

.)

m

Roa

st b

eef

167.

2 1

84

8 22

2 10

71

190.

1 6

7 14

20

3 92

3 M

eatl

oaf

Mea

tloa

f 19

0.1

6 46

3 20

3 6

72

Bak

ed h

am

25.3

3

1547

15

26

3076

1

573

19 1

76

5 F

ried

ch

ick

en

216.

5

1

460

17

1

632

Egg

pro

du

cts

231.

0

1

77

43

1

509

Cor

n-on

-cob

89

.5

17.6

0

36

574

6 10

O

atm

eal

0 66

17

4 24

0 V

eget

. so

up

58.1

21.1

7

900

9 14

18

21

Bac

on

Saus

age

21.1

7

1046

9

14

1967

Gre

en p

eas

79.2

1

1

244

488

733

'The

ro

tary

ove

n w

as u

sed

to b

ake

the

mea

tloa

f

'The

co

nve

ctio

n o

ven

was

use

d t

o b

ake

the

mea

tloa

f P

e


Table 3. Factors affecting energy consumption by electrical, natural gas, and steam equipment in a foodservice system

Signi f icance

Area Equipment Energy Consumption (P=) or ( P O

Receiving Refr igera tors Thermostat s e t t i n g (p = .0001)

and s torage Freezer Thermostat s e t t i n g (p = .0001)

Level

Prepara t ion Refr igera tor Thermostat s e t t i n g (p = .0001)

1 _ _ _ 1 Freezer ---

G r i l l

Deep-fat

f r y e r

Convection

oven

Rotary oven

Steam jacke ted

k e t t l e s

Minutes on per

5-minute i n t e r v a l (p = .0001)

Kilogram mass

of batch (P < . lo )

Percent of basket fill (p = .0001)

Kilogram mass

of batch (P < -01)

Thermostat s e t t i n g (P < -01) Cook respons ib le f o r

product prepara t ion (p < .05)

Kilogram mass

of batch (p = .0001)

Cook respons ib le f o r

product prepara t ion (p = .0001)

Thermostat s e t t i n g (p = .0001)

Cook respons ib le f o r

product prepara t ion (p = .0001)


Table 3. Continued

1

1

--- 1 Jet steamer --- 1 Slicer --- ---

Holding Warming oven Thermostat setting (p = .0001)

1 --- I and service Steam table ---

'No specific variable identified as significantly influencing

the energy consumption by this equipment

recommended capacity, the amount of time and energy required for heat processing per pound tends to increase slightly.

Other significant differences were found in the amount of energy consumed for the deep-fat fryer, rotary oven, and convection oven as the result of the decisions made by the three different cooks concerning the thermostat setting in the heat processing equipment, the quantity of product prepared at one time in a piece of equipment, the length of the heat processing period, and the heat processing equipment used for a recipe. The energy consumed by the grill was influenced significantly by the minutes electric current was flowing during a 5-minute interval, but did not appear to be influenced by menu item quantity or initial temperature of product prepared. This indicated that a noticeable quantity of heat was lost to the atmosphere. Products prepared in steam equipment required the least energy per pound for heat processing.

Variables that did not appear to have significant influence on the energy consumed include the temperature of the product prior to processing in each piece of equipment, percent fill of the warming oven, and the time of day for refrigerators and freezers.

Applications

This food model was developed from on-premise metering during actual food preparation and could be used to follow alternate food product flows. Data from both the food product flow and the energy con-


sumption requirements by equipment could be used to project energy resource requirements in this foodservice facility. In other foodservice facilities, this model could be modified based on the different areas in a foodservice system and the associated equipment in each area. Then this information could be used to make decisions in such areas as equipment scheduling, equipment usage by personnel, and equipment purchasing that would optimize energy usage. For example, for this model, modified energy flow models could be developed such as the one shown in Fig. 2 for meatloaf. Results from these two alternate flows indicate that a greater quantity of energy is required when the rotary oven is used in preparation than when the convection oven is used, other equipment remaining the same along the food product flow. Thus, the least energy intensive preparation oven, the convection oven, should be identified on the standardized recipe as the preferred oven to use in this facility. Simi- lar analyses for the least energy intensive food product flow of many other items could be developed.

The methodology for this research could be used to assess the energy- use effectiveness between various types of foodservice systems, especially if one is designing or contemplating the change of a foodservice system. The model could be modified to represent the areas in alternate systems and the associated equipment where the modified model and the energy consumption data for the equipment could be used to study the energy required for food-product flow alternatives. In essence, this methodology could be used as one approach for structuring a more adequate data base relative to energy usage.

Additionally, the cost of each energy flow should be calculated because, depending on the cost of available energy resources, the least energy intensive food-product flow may be the most expensive flow depending on the cost of the energy resources. Development of an energy costing model would assist in the evaluation of potential food product flows.

Limitations

Limitations to this study include the lack of control over many variables beginning with personnel and food production decisions made by personnel. Even though standardized recipes were used, personnel may modify the type, market form or quantity of ingredients used or the pro- cedures used to prepare a product. Thus, future research should investigate the energy consumption for processing menu items when only one


Receiving

1.170 Btu

(Receiving and Storage)

135,696 Btu 88,003 Btu (Preparation)

convection Preparation

J 1

38,621 Btu

(Holding and Service)

'refrigerator

2warming oven

175,487 Mean Total Btu (923 Btullb. Meatloaf)a

127,794 Mean Total Btu (672 Btu/lb. Meatloaf)b 3otary oven used convection oven used

FIG. 2. SEQUENTIAL ENERGY CONSUMPTION THROUGH THE FOOD PRODUCT FLOW FOR MEATLOAF (760 servings) (190.1 lb)


person prepares a product from the same market form of ingredients several times along the same food product flow with the same or varia- tions of equipment.

Also, variability in the maintenance of equipment would need to be controlled. The older the equipment, the less maintained the equipment, and subsequently, the less energy efficient the equipment tends to be. Because the equipment is perceived as old or not well maintained, personnel may alter the recommend thermostat settings of the equipment to obtain an acceptable finished product.

Finally, practitioners may not have the luxury of being able to choose between two or more types of equipment for heat processing menu items. So being able to identify the most energy efficient food product flow may not be practical. Another reason for this impracticality might be the amount of time one can devote to the analysis of food product flow and the subsequent expense of this analysis. Both the expense and time required for this analysis might be modified by adapting this methodology and the associated energy consumption data for equipment to com- puter software.

CONCLUSIONS

This present study is descriptive of energy consumption in an operating foodservice facility. A schematic energy flow decision model was developed that could be used to analyze the most effective and efficient food product flow for a menu item in this foodservice facility. Alternate flows could be analyzed in order to minimize the energy required to store, prepare, hold, and serve the menu item while maintaining the qual- ity of the food served. Various factors were identified as having significant influences on the energy consumption by equipment such as the quantity of product prepared in the convection oven and deep-fat fryer, rotary and warming ovens. Decisions concerning how equipment was used by the food preparation personnel were another significant influence on the amount of energy required to prepare a product in the con- vention and rotary ovens, and the deep-fat fryer. The number of minutes that current was flowing during each 5-minute period in the grill was a significant variable which indicates that the area exposed to the atmosphere influences the energy consumption. Each of these noticable influences should be investigated further.

The methodology developed could be used to analyze the energy consumption for the processing of menu items, to forecast energy consumption, and to determine the most efficient and effective food product flow


in a foodservice facility. From this data, decisions concerning energy conservation could be made about purchasing, scheduling, and equipment usage, processing menu items, and developing appropriate employee training programs.

REFERENCES

BARR, A. J., GOODNIGHT, J. H., SALL, J. P. and HELWIG, J. T. 1976. A User’s Guide to SAS-76. SAS Institute, Inc., Raleigh, NC.

DWYER, S. J . , UNKLESBAY, K., UNKLESBAY, N. and DUNLAP, C. 1977. Identification of Major Areas of Energy Utilization in the Food Processing/ Food Service Industry. University of Missouri, Columbia, MO.

MCPROUD, L. M. 1977. Energy management in production of entrees in hos- pital foodservice systems. Unpublished Ph.D. thesis, University of Wisconsin, Madison, WI.

NATIONAL RESTAURANT ASSOCIATION 1979. Personal communication. Washington, DC: NRA, March.

energy consumption assessment in a conventional foodservice system

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