A Novel Macro and Micro Scheduling Model for Regulated Safety Inspections Based on Probability Integral Transform and Modified Bin Packing Algorithm

• Main Author: Mohamed A. Zytoon
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Access
• Subjects: Scheduling; macro scheduling; micro scheduling; probability integral transform; percentile rank; bin packing
• Online Access: https://ieeexplore.ieee.org/document/9439913/
• ISSN: 2169-3536

Occupational safety and health (OSH) inspection is an essential element of OSH regulatory enforcement programs. The effectiveness of regulated OSH inspections is dependent on many factors of which proper planning and scheduling of inspections, and optimum utilization of inspectors are extremely important. In spite of this, there is no published scheduling model to solve the problem of regulated safety inspections. Absence of such models negatively affected the performance of safety inspectorates in many countries which is manifested by low portion of firms being inspected over long periods of time. For these, there is urgent need to introduce new scheduling models to solve such problem that has distinctive characteristics compared to the scheduling problems in other fields. The current paper presents a novel hybrid macro and micro scheduling approach that is based on Probability Integral Transform (PIT) and a modified Bin Packing algorithm that address the Inspector Utilization Problem with Firm Inspection Sharing (IUPFISh). The PIT-IUPFISh model consists of uniform long-term macro scheduling of firms for inspection using PIT approach coupled with short-term micro scheduling of firm inspection using the IUPFISh algorithm to determine the daily scheduling of the firms and inspectors so that maximum utilization of inspectors is achieved. A case study was presented to show the application of the proposed model. The results indicate that the application of the proposed model can improve OSH inspectorate performance through improved planning and scheduling as well as maximizing effective utilization of manpower.