Burn-in policies for products having dormant states

Many systems might have a long time dormant period, during which the systems are not operated. For example, most building services products are installed while a building is constructed, but they are not operated until the building is commissioned. Warranty terms for such products may cover the time starting from their installation times to the end of their warranty periods. Prior to the commissioning of the building, the building services products are protected by warranty although they are not operating. Developing optimal burn-in policies for such products is important when warranty cost is analysed. This paper considers two burn-in policies, which incur different burn-in costs, and have different burn-in effects on the products. A special case about the relationship between the failure rates of the products at the dormant state and at the operating state is presented. Numerical examples compare the mean total warranty costs of these two burn-in policies.

Burn in policies for products having dormant states

Constructing a building is a long process which can take several years. Most building services products are installed while a building is constructed, but they are not operated until the building is commissioned. The warranty term for the building service systems may cover the time starting from their installation to the end of the warranty period. Prior to the commissioning of the building, the building services systems are protected by warranty although they are not operated. The bum in time for such systems is important when warranty costs is analyzed. In this paper, warranty cost models for products with burn in periods are presented. Two burn in policies are developed to optimize the total mean warranty cost. A special case on the relationship between the failure rates of the product at the dormant state and at the I operating state is presented.

Optimal maintenance policies under different operational schedules

In the reliability literature, maintenance time is usually ignored during the optimization of maintenance policies. In some scenarios, costs due to system failures may vary with time, and the ignorance of maintenance time will lead to unrealistic results. This paper develops maintenance policies for such situations where the system under study operates iteratively at two successive states: up or down. The costs due to system failure at the up state consist of both business losses & maintenance costs, whereas those at the down state only include maintenance costs. We consider three models: Model A, B, and C: Model A makes only corrective maintenance (CM). Model B performs imperfect preventive maintenance (PM) sequentially, and CM. Model C executes PM periodically, and CM; this PM can restore the system as good as the state just after the latest CM. The CM in this paper is imperfect repair. Finally, the impact of these maintenance policies is illustrated through numerical examples.

Risk pricing practices in finance, insurance and construction

A review of current risk pricing practices in the financial, insurance and construction sectors is conducted through a comprehensive literature review. The purpose was to inform a study on risk and price in the tendering processes of contractors: specifically, how contractors take account of risk when they are calculating their bids for construction work. The reference to mainstream literature was in view of construction management research as a field of application rather than a fundamental academic discipline. Analytical models are used for risk pricing in the financial sector. Certain mathematical laws and principles of insurance are used to price risk in the insurance sector. construction contractors and practitioners are described to traditionally price allowances for project risk using mechanisms such as intuition and experience. Project risk analysis models have proliferated in recent years. However, they are rarely used because of problems practitioners face when confronted with them. A discussion of practices across the three sectors shows that the construction industry does not approach risk according to the sophisticated mechanisms of the two other sectors. This is not a poor situation in itself. However, knowledge transfer from finance and insurance can help construction practitioners. But also, formal risk models for contractors should be informed by the commercial exigencies and unique characteristics of the construction sector.