Quantifying the value of ownership of yield analysis technologies

Abstract

Abstract-A model based on information theory, which allows yield managers to determine optimal portfolio of yield analysis technologies for both the R&D and volume production environments, is presented. The information extraction per experimentation cycle and information extraction per unit time serve as benchmarking metrics for yield learning. They enable yield managers to make objective comparisons of apparently unrelated technologies. Combinations of four yield analysis tools-electrical testing, automatic defect classification, spatial signature analysis and wafer position analysis-are examined in detail to determine the relative value of ownership of different yield analysis technologies.

Characterizing the value of technological knowledge for lean manufacturing

“…The primary differentiators of this model are the incorporation of value of ownership [1], [11], [15] and the model's ability to span the complete investment horizon of a semiconductor process lifecycle. These features allow manufacturing managers to determine the true value of lean manufacturing practices over time.…”

Unnoticed Effects of Inspection Errors and a Quality Paradox

“…Further, consider the contribution to costs of this part of Feigenbaum's hidden plant . Suppose that seven inspections are added, say after each 10 operations (as in, e.g., Weber et al; Rodriguez‐Verjan et al). If α = 5% for each inspection, then the good intention results in a yield decrease to 34.55%.…”

“…The other 608 units are falsely rejected. These repercussions are overlooked by the technology managers of Weber et al and by Rodriguez‐Verjan et al who have considered adding 20 or 50 inspection operations to the processes, which already include inspections to reduce the number of defectives. Actually, no work could be found, which shows that inspections result in more defective units.…”

“…Inspections are commonly used to improve quality. In practice, ‘the potentially dire consequences of not detecting an electrical fault early during the process have motivated technology managers in the semiconductor industry to introduce an inspection step after about every 10 process steps.’ Researchers stated that ‘if new inspection operations are added, the delay to get this measurement result is reduced, and the wafer at risk could thus also be reduced.’ Inspections are considered in this study too.…”

Yield learning and the sources of profitability in high technology manufacturing and process development

“…The amount of information extracted per leaming cycle and per unit time can serve as a metric for learning rate [24] At all stages of process development semiconductor manufacturers design for diagnosability (DtD), in order to accelerate the learning rate. DfD practices include designing microelectronic test structures into products and inspectioddiagnostic steps into the process, as well as partitioning the solution space of a problem -the area where the solution of a problem must lie -by running a manufacturing baseline in parallel with a process R&D effort.…”