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Analysis of laundry industry. Extended energy survey reports 1984-1989

Technical Report:

Abstract

There are 12 Extended Energy Surveys (EES) from United Kingdom industrial laundries analysed in this report. Three of these are hospital laundries, one is stone washing and bleaching jeans, and the remainder are commerical laundries processing a wide range of goods. Typical products of a commercial laundry are bed linen and table linen from hotels, workwear, industrial wiping cloths, cabinet towels, and dust control mats. The 12 sites represent about 5% of the energy used in the fabric care industry. They cover the whole range of sites from the small independent laundry employing 25 people to the largest of commercial sites employing 170 people. The mean specific energy consumption is 4.77kg of steam per kg of work processed. Potential energy savings of Pound 0.36 million/year were identified in the 12 reports. These savings were classified in two ways, by type of measure and by cost. The most important measures were energy management, heat recovery, boilers, and steam distribution. In terms of energy savings, 64% were attributable to techniques costing Pound 5k or more. These were mainly heat recovery measures. All the measures yielded a payback of less than 2 years except for some of the heat recovery measures. The ratio  More>>
Authors:
Publication Date:
Jun 01, 1991
Product Type:
Technical Report
Report Number:
ETSU-R-68
Reference Number:
SCA: 320301; 320303; PA: GB-92:053424; SN: 93000926077
Resource Relation:
Other Information: PBD: Jun 1991
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; LAUNDRIES; ENERGY CONSERVATION; UNITED KINGDOM; ENERGY MANAGEMENT; HEAT RECOVERY; BOILERS; STEAM SYSTEMS; ENERGY CONSUMPTION; COST; PAYBACK PERIOD; SURVEYS; 320301; 320303; ENERGY SOURCES; EQUIPMENT AND PROCESSES
OSTI ID:
10117240
Research Organizations:
AEA Environment and Energy, Harwell (United Kingdom)
Country of Origin:
United Kingdom
Language:
English
Other Identifying Numbers:
Other: ON: DE93759158; TRN: GB9253424
Availability:
OSTI; NTIS (US Sales Only)
Submitting Site:
GB
Size:
11 p.
Announcement Date:
Jun 30, 2005

Technical Report:

Citation Formats

Slade, M. Analysis of laundry industry. Extended energy survey reports 1984-1989. United Kingdom: N. p., 1991. Web.
Slade, M. Analysis of laundry industry. Extended energy survey reports 1984-1989. United Kingdom.
Slade, M. 1991. "Analysis of laundry industry. Extended energy survey reports 1984-1989." United Kingdom.
@misc{etde_10117240,
title = {Analysis of laundry industry. Extended energy survey reports 1984-1989}
author = {Slade, M}
abstractNote = {There are 12 Extended Energy Surveys (EES) from United Kingdom industrial laundries analysed in this report. Three of these are hospital laundries, one is stone washing and bleaching jeans, and the remainder are commerical laundries processing a wide range of goods. Typical products of a commercial laundry are bed linen and table linen from hotels, workwear, industrial wiping cloths, cabinet towels, and dust control mats. The 12 sites represent about 5% of the energy used in the fabric care industry. They cover the whole range of sites from the small independent laundry employing 25 people to the largest of commercial sites employing 170 people. The mean specific energy consumption is 4.77kg of steam per kg of work processed. Potential energy savings of Pound 0.36 million/year were identified in the 12 reports. These savings were classified in two ways, by type of measure and by cost. The most important measures were energy management, heat recovery, boilers, and steam distribution. In terms of energy savings, 64% were attributable to techniques costing Pound 5k or more. These were mainly heat recovery measures. All the measures yielded a payback of less than 2 years except for some of the heat recovery measures. The ratio of national benefit to Government cost for the 12 EES`s would have been approximately 14:1 if all recommended measures had been undertaken. (author).}
place = {United Kingdom}
year = {1991}
month = {Jun}
}