Abstract: At present, a manufacture system is regulated using the statistical method. The statistical method is based on probability and statistics theory. Normal distribution is required, the standard deviation and the coverage factor are beforehand certain for the output of the manufacture system, and therefore it will be very difficult to resolve the problems of the Regulation and error forecast of the manufacture system with non-normal distributions, unknown or non-comprehensive information by means of the classical statistical theory. Therefore, a novel method is proposed. This method is the non-statistical method based on fuzzy-set theory. By using this method, many typical and untypable problems, such as normal distribution, uniform distribution, and commingle distributions, can be researched, the disperse interval of the systemic output can be straightway estimated without any known characteristic parameter such as the standard deviation and the coverage factor. Influence of the random error’s change in size and direction on the systemic output can be roundly and truly described because the algorithm of fuzzy interval-data is introduced, and the average values and the maximum difference-values of fuzzy interval-data are considered in processing the commence and conclude data. Computer imitation and manufacture cases indicate the very small error and the very high veracity of estimating for the systemic output using the non-statistical method proposed.

Key words: Error, Forecast, Fuzzy-set theory, Manufacture system, Non-statistical theory, Regulation