航空武器装备项目延期原因及对策研究

在分析航空武器装备项目中常见的“返工”现象的基础上,分析了引起航空武器装备项目延期的主要原因,针对这些原因提出解决的对策,并针对耦合型作业引入一种异于并行工程的全新的解决思路。     

Endogenous Adaptation: The Effects of Technology Position and Planning Mode on IT‐Enabled Change*

The redesign of information technology (IT)‐enabled work processes often necessitates fundamental design changes to the intended work process, the IT platform hosting the work process, or both. Research suggests that such design changes often can be traced to earlier decisions involving endogenous adaptation or internal organizational change. Two such decisions are a firm's technology position and planning mode. This study examines the relationship between technology position and planning mode in predicting the magnitude of design change in process redesign projects. The conceptual frame applied in examining these relationships involves a synthesis of Miles and Snow's adaptive cycle with elements central to concurrent engineering. Our results indicate that the magnitude of design change is related to differences in technology position and planning mode. To effectively implement organizational change, firms must leverage their IT platform by carefully timing IT investments in accordance with their adopted technology position. Directing the trajectory of a firm's IT platform and deploying it so as to complement the firm's technology position reduces design uncertainty, promoting reengineering success.     

A production model for deteriorating items with stochastic preventive maintenance time and rework process with FIFO rule

Due to unreliable production facility and stochastic preventive maintenance, deriving an optimal production inventory decision in practice is very complicated. In this paper, we develop a production model for deteriorating items with stochastic preventive maintenance time and rework using the first in first out (FIFO) rule. From our literature search, no study has been done on the above problem. The problem is solved using a simple search procedure; this makes it more practical for use by industries. Two case examples using uniform and exponential distribution preventive maintenance time are applied. Examples and sensitivity analysis are conducted for each case. The results show that rework and preventive maintenance time have significant affected the total cost and the optimal production time. This provides helpful managerial insights to help management in making smart decisions.