Qual­ity and re­li­a­bil­ity de­fined in dif­fer­ent ways

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Def­i­ni­tion 1: Con­for­mance to re­quire­ments—given by Crosby Def­i­ni­tion 2: Free­dom from de­fi­cien­cies or fit­ness for use—given by Ju­ran Def­i­ni­tion 3: De­gree to which a set of in­her­ent char­ac­ter­is­tics of a prod­uct ful­fils re­quire­ments—given by In­ter­na­tional Stan­dards Or­ga­ni­za­tion


The prob­a­bil­ity that an item per­forms its ‘de­signed func­tion’ for a ‘stated pe­riod of time,’ when op­er­ated un­der ‘stated con­di­tions.’ It is a num­ber be­tween 0 and 1.

Let us try to un­der­stand sta­tis­tics-based prob­a­bilis­tic def­i­ni­tion of re­li­a­bil­ity more clearly. Say, a man­u­fac­turer sold a thou­sand re­frig­er­a­tors in a day all over the coun­try. All started func­tion­ing on the same day. All were used as per the pre­scribed op­er­at­ing pro­ce­dure in the pre­scribed en­vi­ron­ment for three years. Let us as­sume that 30 re­frig­er­a­tors in the batch failed in three years. It means that the prob­a­bil­ity of sur­vival for three years is (100030)/1000=970/1000=0.97.

Hence 0.97 is the re­li­a­bil­ity for three-year time pe­riod for these re­frig­er­a­tors. The higher the re­li­a­bil­ity, lesser the prob­a­bil­ity of fail­ure.

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