Chen and Chung (1996) addressed the problem of the joint determination of the optimal process mean and production run for an industrial process. Their study considered a product with an upper and a lower specification limit. The optimal process mean and optimal production run were obtained by balancing the profit of meeting and not meeting the specification limits. However, Chen and Chung did not consider the quality cost for the product within the specification limits. The present paper revisits the problem and incorporates the quality cost by introducing a Taguchi loss function for determining simultaneously the optimal process mean and production run. As per Chen and Chung, the present paper assumes a 100% inspection scheme. It also investigates the differences between Chen and Chung's approach and the Reward Theorem approach. A sample inspection scheme is also proposed. Numerical examples are provided to demonstrate the application of the model. A sensitivity analysis of the model is provided. Some new directions for further research are also outlined.

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PurposeIn this work, a framework for assessing construction contractors' performance in Saudi Arabia is developed. Usually, a contractor's assessment is based on financial aspects, which are lagging indicators in nature, and can ignore other nonfinancial aspects. Hence, a more detailed contractors' assessment framework is needed for the construction industry in Saudi Arabia. A framework that integrates financial and nonfinancial aspects in one model will enable contractors to better benchmark their performance to the rest of Saudi Arabia's construction industry.Design/methodology/approachInitially, the literature is reviewed and the most commonly used key performance indicators (KPIs) are identified and surveyed through contractors’ feedback to ensure their proper alignment with Saudi Arabia’s construction industry. The adopted set of KPIs will be further prioritized through the relative importance index (RII) method based on the surveyed contractors’ perceptions. Furthermore, the important set of KPIs will be factored into various groups using principle component analysis (PCA). Finally, the findings are validated through expert judgment.FindingsAll key performance indicators (KPIs) have proven to be significant, except for the environmental factor, which happens to be nonsignificant and hence has been omitted from further consideration. The remaining KPIs have been factored through the principle component analysis method. Five generic dimensions were identified: Performance, Satisfaction, Actual Metrics, Estimated Metrics and Compliance. The model has been validated by expert feedback, and it was found to be reliable.Originality/valueThe proposed model establishes an assessment framework to aid building construction contractors in assessing their performance in real time, in addition to postconstruction assessment for business development and retrofitting purposes.

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It is common in the integrated targeting inventory literature to assume 100% inspection. Yet, sampling inspection is still a valid alternative in numerous situations. Inspection time has been assumed negligible in the literature of integrated inventory and sampling inspection. Neglecting inspection time is unrealistic, especially when rejected lots are sent for 100% inspection. This research work integrates process targeting, production lot-sizing and inspection. Given a scenario of a producer and distributer, the objective is to determine the optimal mean setting at the producer, the production lot size to be produced and shipped to the distributor and the reorder point at the distributor under a given sampling inspection plan. To the best of the authors’ knowledge, sampling inspection and its associated costs are rarely addressed in integrated supply chain models, and have never been addressed in integrated models with controllable production rates. Numerical illustrations using an efficient solution technique are presented to highlight the impact of various model parameters. The results indicated that inspection time has a significant impact on the total cost of the developed model, especially, when tightened inspection plans are used.