Job configuration in semiconductor manufacturing refers to the process of configuring silicon wafers in terms of chip types and volumes, organizing collections of wafers into jobs, and determining the volume of jobs to be released into the production line, The difficulties of job configuration lie in the random yield loss, the numerous technological constraints, and the rigid set serviceability, requirement (i.e., demand must be met in terms of all chip types), Motivated by the configuration problems in the ''early-user hardware'' development programs at some IBM plants, we develop here a systematic approach to job configuration, The centerpiece of the approach is a careful treatment of the set serviceability constraint, in terms of both probability and expectation, It solves the job configuration problem as separable convex programs using marginal allocation algorithms, Through numerical examples, we demonstrate that by allowing diversity of chip tyes at either the job- or the wafer-level, higher serviceability can be achieved using fewer wafers.
