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This paper aims to propose a new approach to setting the control limits to promote the control performance of the cumulative count of conforming chart (CCC-r chart), in terms of the average number of items inspected (ANI).

In contemporary high-yield manufacturing processes, the CCC-r chart is often an alternative of p charts or np charts for monitoring the fraction nonconforming (p). When a CCC-r chart is used, the traditional approach based on the equal-tail probabilities to setting control limits demonstrates a poor performance in terms of ANI as p deviates upward from its nominal value p ₀. To improve the performance of CCC-r charts, this research uses a search method based on some analytical results to find the control limits such that the in-control ANI (ANI ₀) is near-maximal and near-unbiased.

Analytical validation confirms that the proposed approach outperforms the traditional one in terms of the maximum and the unbiasedness of ANI ₀. When p ₀ is not given, simulation results show that the minimum-variance unbiased estimator tends to perform better than the maximum likelihood estimator.

This study numerically shows that the use of the proposed approach achieves the goal of the near-maximal and near-unbiased ANI ₀, and hence improves the performance of CCC-r charts. In addition, because the proposed approach is computational intensive, this study also develops a Visual Basic project to help practitioners obtain the control limits using the proposed approach.

In the early industrial age which with high intensity of machine and labor, using financial measurement index was good enough to tie in company’s mechanization and philosophy of management and been in efficiency. But being comply with “New Economic age,” a new economic environment is full of knowledge and information, the enterprise competition had changed from tangible assets, plants to intangible innovation ability of knowledge. As recognizing the new tendency by enterprise, they value gradually the growth and influence from learning. Practice of organization learning not only needs firm structure and be in coordination with both hardware and software, but also needs an affect measurement model to offer enterprise to estimate learning performance. It’s a good instrument of financial performance measure mold in the past years, But it’s for measuring the past, couldn’t formulate enterprise trend to future, hard to estimate investment for future, such as development of products, organization learning, knowledge management etc, as which intangible assets and knowledge ability just the key factors of being win around competition environment in the future. In 1992, Kaplan and Norton brought up Balance Scorecard (BSC) on Harvard Business Review, as an instrument helping enterprise to measure performance, which is being considered to be a most influence management instrument. It added non‐financial index such as customer, internal process and learning growth besides traditional financial index, as offering enterprise an index to measure and manage intangible assets and intellectual property. As being aware of organization learning is hard to be ignored in the new economic age, this research is based on learning and growth of BSC, and citing one national material company try to let the most difficult measurement performance of organization learning, to be estimate through BSC, analyze of factor and individual case, to discuss the company how to make the related strategy and vision of organization learning to develop learning and growth of the structure of BSC, subject the matter of out put factors to be discussed, and measure the outcomes as a result of research. The research affect offers (1) the base implement procedure of carrying out BSC; (2) the reference of formulating measurement index while enterprise using BSC to estimate performance of organization learning; (3) the possibility bottleneck maybe forcing while carrying out BSC, to be an improvement or preventive for enterprise.