System Availability Optimization: Integrating Quantity Discounts and Delivery Lead Time Considerations

TL;DR

This paper presents a nonlinear binary programming model that optimizes system component supplier selection by considering quantity discounts, delivery lead times, and construction delays to maximize system availability and minimize costs.

Contribution

It introduces a novel integration of Markov process results into nonlinear binary programming for comprehensive system lifecycle optimization.

Findings

Optimal supplier orders for industrial system components identified.

The approach balances construction costs and operational availability effectively.

Model improves system performance by considering delivery and discount factors.

Abstract

Purpose: The model allocates the system components orders to the suppliers to minimize the parts price and the system construction delay penalties and maximize the system availability during its use. It considers the quantity-based discount and variation of delivery lead time by ordering similar components. The model also reflects the prerequisite relationships between construction activities and calculates the delay penalty resulting from parts delivery lead time. Design/methodology/approach: This research presents a model for selecting suppliers of components of an industrial series-parallel multi-state system. A nonlinear binary mathematical program uses the Markov process results to select system components. It minimizes the total system construction phase costs, including the components' price, and the system construction delay penalty, and the system exploitation phase costs, including the system shutdown and working at half capacity. Findings: The model allocates the optimal orders for a typical industrial system's components, composing four elements. The proposed approach combines the nonlinear binary program and the Markov process results to optimize the system life cycle parameters, including the system construction cost and operational availability. Originality/value: Using the Markov chain results in binary nonlinear mathematical programming, this study attempts to strike the right balance between the construction phase's objectives and an industrial unit's operation phase.