Wartime industrial logistics information integration: Framework and application in optimizing deployment and formation of military logistics platforms

Abstract

Industrial logistics system is one of the key objects of industrial informatization, and analysis on this system is an important task of industrial information integration. According to the concept and principle of industrial information integration engineering, we present a five-layered framework of wartime industrial logistics information integration, and form an analysis of wartime industrial logistics system from the perspective of industrial information integration. To provide resolutions to the problems of optimizing deployment and formation of resources in wartime industrial logistics system (e.g., military logistics platforms [MLPs]), we conduct a typical application of this framework. As the research objects of the fourth layer, war statistics, mathematical calculations and simulation experiment are designed as the means by which descriptive analysis, predictive analysis and prescriptive analysis at the fifth layer can be implemented, respectively. Accordingly, the battle damage repair efficiency-oriented optimal decisions model of using MLPs are built. Results show that our study forms a systematic procedure for wartime industrial logistics information integration, thus obtaining more decision support and greater reference value for wartime industrial logistics.

Introduction

Multiple stakeholders have increased their demand for research on industrial information integration due to its strategic importance [1]. Given that industrial logistics is in substance related to the use of equipment and maintenance materials, industrial logistics system is one of the key objects of industrial informatization, and analysis on this system is an important task of industrial information integration. Therefore, the optimal use of resources in industrial logistics system is a prerequisite for industrial information integration.

The word “logistics” originates from the military discipline. The divisions in the military are responsible for the supply of necessary arms, ammunition, tents and rations as and when they are needed [2]. Wartime industrial logistics focuses on the wartime supply of military materials. In the performance of these tasks, a commander must make some analytical decisions by using the various types of wartime industrial logistics data. Recently, many researchers in technical and social fields have attached importance to data analytics [3], [4], [5]. In this study, we introduce “data analytics” and define “wartime industrial logistics data analytics”, which means the technology that a commander requires to handle wartime industrial logistics data at controlled scales.

Equipment support is one of essential tasks in wartime industrial logistics. Mobile equipment support refers to the mode of recovering and repairing equipment by logistics vehicles, which can be defined as military logistics platforms (MLPs), maneuvering to the support place and providing equipment support. This mechanism is the basic mode for the MLPs to provide battlefield support, in particular maintenance mission under enemy fire strike. Given that the logistics unit mainly provides material supply support and equipment technical support for combat units, it has limited self-defense capability and weak combat power. The MLPs that carry support personnel become the key targets by enemy strike. During the execution of wartime industrial logistics, the combat opportunity is transient due to the urgent time, and different military logistics modes should be adopted in accordance with the battle damage repair tasks and threats of enemy situations to reasonably allocate and use the MLPs and flexibly organize the logistics resources. If the MLPs used in operation are not enough, then the damaged equipment cannot be repaired and utilized in combat, and the regeneration of combat power will be affected. If the MLPs used at one combat direction are more than they need, then it may weaken the support capability at other combat directions. Meanwhile, the additional support equipment and apparent targets will increase the probability of enemy strike. Therefore, how to optimize deployment and formation of MLPs is one of the key subjects for decision-making of wartime logistics command.

We present the framework of wartime industrial logistics information integration and focus on its application in optimal decisions for using MLPs. This work is based on related studies on data analytics in industrial engineering, technical systems, and social fields [2], [3], [4], [5]. However, this work differs from these studies by providing useful insights into military field application of data analytics. Our work centers on the following topics: developing a systematic procedure of wartime industrial logistics information integration, presenting war statistics based on collected historical combat data, as well as performing quantitative calculation and computer simulation demonstration for this procedure and its application.

The rest of the paper is organized as follows. Section 2 introduces the current related work. Section 3 presents the problem description and research methodology. Sections 4, 5, and 6 provide the data analytics-oriented analysis, modeling, and simulation in details, in which descriptive, predictive and prescriptive analytics are illustrated, respectively. Section 7 summarizes the conclusion and describes some future work directions.