Before the Roof Caves in: A Predictive Model for Physical Plant Renewal. APPA Technical Paper.

Autor/inn/en	Hutson, Robert E.; Biedenweg, Frederick M.
Institution	Association of Physical Plant Administrators of Universities and Colleges, Washington, DC.
Titel	Before the Roof Caves in: A Predictive Model for Physical Plant Renewal. APPA Technical Paper.
Quelle	30 (1982) 7, S.7-10 (6 Seiten)Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; Monographie
Schlagwörter	Campus Planning; College Buildings; Construction Programs; Educational Facilities Improvement; Evaluation Methods; Higher Education; Mathematical Models; Prediction; School Maintenance; Statistical Analysis + Suchen Sie Ihr Suchwort? College; Colleges; University; Universities; Infrastructure; Planning; Hochschule; Fachhochschule; Universität; Infrastruktur; Planung; Planungsprozess; Building; Buildings; Gebäude; Baumaßnahme; Hochschulbildung; Hochschulsystem; Hochschulwesen; Mathematical model; Mathematisches Modell; Vorhersage; Statistische Analyse
Abstract	A quantitative method developed at Stanford University that addresses programmatically the short- and long-term needs of the college physical plant is discussed. The approach allows the administrator to accurately assess funding resources for the maintenance program in conjunction with academic and construction programs. A special task force at the university established a conceptual framework based on predictable cycles for facility renewal and replacement. The task force identified five features that would affect the wearing out of the facility and system and the resulting replacement/renewal costs. These five features were: facility subsystems, facility type, subsystem life cycles, subsystem cost, and date of facility construction. These features were quantified by analyzing the existing physical plant and by researching available data. The objective was to forecast future renewal and replacment requirements. Using data that reflected actual conditions at the university, it was possible to model accurately Stanford's physical plant and to simulate the future renewal/replacement requirements. Each of the five features and resulting data set are discussed in detail in order to outline the methodology used for developing the data. (SW)
Erfasst von	ERIC (Education Resources Information Center), Washington, DC