Decision Problem on Imperfect Inspections Combined under Two-Stage Inspection Policy

Although one can presently observe great development in the methods for diagnosing conditions of technical systems, inspections which are not 100% accurate are still common in industry. If there are multiple available inspection methods which differ in accuracy of diagnosis, cost, or testing time, the answer for the question: which inspection method should be chosen is not a simple task. This paper addresses the problem and proposes a two-stage inspection policy model whose aim is to combine inspection methods that differ in their accuracy and cost features. The two-stage policy models that have been used so far in the literature assume that the second stage of an inspection is perfect, which is not always possible or profitable. For this reason, the mathematical model of the two-stage inspection policy with not-necessarily-perfect second stage is developed here, and its results are presented for the case study of diagnosing sealing in a hydraulic cylinder. The example proved that the application of mixed imperfect inspections could decrease maintenance cost, compared to the one-stage perfect inspection policy, by up to 35%. The paper also formulates a set of rules that support decision making while searching for cost-effective parameters of the two-stage policy. Their application is confirmed by a numerical example, which shows their potential in suboptimization of the proposed policy.

Optimal Periodic Inspection Policy for a Parallel System Subject to Continuous Bi-Levels Degradation

Each system goes through several intermediate states between its initial state and the failure state, which are called degradation states. In addition, knowing these intermediate states allows us the building of an effective maintenance plan for the system under consideration. In this paper, we have considered a two-component parallel system where each component is subjected to two levels of degradation. Our first objective is to identify the mathematical (probabilistic) model associated with this system and this when the hypothesis of periodic inspection of the system is retained. Then, the main idea is to build the economic model encompassing the different average costs (inspection costs, preventive maintenance costs and corrective maintenance costs) spent during a renewal cycle. The latter will allow us to determine the optimal “inspection interval” while minimizing the average global-cost spent. Finally, in order to illustrate and analyze the sensitivity of the optimal inspection policy to the various maintenance costs, numerical examples are presented.

Impact Analysis of Large-Scale Environmental Spot Inspection Policy on Green Innovation: Evidence From China

The spot inspection policy has been widely applied in environmental protection in China. This paper collects environmental enforcement announcements and green patent data published by Chinese government agencies from 2006 to 2015. First, it studies the impact of spot inspection on green innovation with the spatial Durbin model. Then, it analyzes spatial heterogeneity according to the eastern, central, and western regions including 29 provinces. The spot inspection policy significantly increases the green innovation of a current region with a negative spillover effect on neighboring regions. Even though this policy has the best performance in the eastern region, it leads to pollution transfer into the western region, while being ineffective in the central region. Further, analysis on the spatial spillover effects of the 29 provinces proves that 21 provinces have a positive spillover effect, while eight provinces have a negative spillover effect. The research study shows that although spot inspection is generally beneficial to green innovation, pollution transfer and policy failure exist because of spatial heterogeneity.

Modelling of Materials Management System for Cross-country Pipeline Project from Client’s Perspective

In managing a pipeline construction project, the selection of vendors, the procurement of materials, developing optimum inspection policy, planning and managing the inflow of materials at different point of time, managing desired level of inventory, proper storage of materials, managing outflow of materials backed up with flow less transportation process and minimizing of wastages at the construction site are big challenges faced by all clients of a cross-country pipeline project. Therefore, on this backdrop, an attempt has been made to construct a materials management system that is applicable for the construction of a cross-country pipeline project. In this context, the objective of this research work is to model the materials management system by applying different methods to take care of vendor selection, materials inspection, materials storage, materials transportation, controlling stock, and managing wastage of materials at the project construction. The methods used for conducting this research work are Garret’s rating technique, and physical system theory (PST). After reviewing different problems faced by the Morbi–Mundra pipeline project team of Gujarat State Petronet Ltd (GSPL), it is expected that the model developed would remove problems faced by GSPL and would facilitate different clients of a pipeline project to complete the project without any time and cost overrun.

The economic order quantity model with inspection policy of zero-defect single sampling

PurposeThis paper proposes a new inventory model with inspection policy because in practice the received orders may contain non- conforming (NC) items. So, a buyer who receive an order from a supplier should use an inspection policy.Design/methodology/approachThe inspection policy is assumed to be zero-defect single sampling. Under this policy a lot is accepted only if no defect has been identified in the inspected sample. The fraction of NC is assumed to be a random variable following a Binomial distribution and the number of NC items detected by inspection assumed to be a random variable, which follows a hypergeometric distribution. Order quantity and sample size are the two decision variables. A solution procedure is presented for the proposed model. The proposed procedure presents the optimal solution.FindingsNumerical examples presented to illustrate the procedure outlined for the proposed model and its applicability. The results of numerical examples and comparing them with traditional EOQ model reveal that by the proposed model, the buyer could reduce total cost that shows the efficiency and validity of the proposed model.Originality/valueThe novelty of this paper is the new proposed model that considers inspection policy in inventory management. The proposed model determines sample size as well as order quantity to consider both subject of inventory management and quality control, simultaneously.