Data-Driven Process Reengineering and Optimization Using a Simulation and Verification Technique

Abstract

Process reengineering (PR) in manufacturing organizations is a big challenge, as shown by the high rate of failure. This research investigated different approaches to process reengineering to identify limitations and propose a new strategy to increase the success rate. The proposed methodology integrates data as a procedure for process identification (PI) and mapping and incorporates process verification to analyze the changes made in a specific process. The study identifies interdependency within the manufacturing process (MP) and proposes a generic process reengineering approach that uses simulation and analysis of production line data as a method for understanding the changes required to optimize the process. The paper discusses the methodology implementation technique as well as process identification and the process mapping technique using simulation tools. It provides an improved data-driven process reengineering framework that incorporates process verification. Based on the proposed model, the study investigates a production line process using the WITNESS Horizon 21 simulation package and analyse the efficiency of data-driven process reengineering and process verification in terms of implementing changes.

Integration of Data-Driven Process Re-Engineering and Process Interdependence for Manufacturing Optimization Supported by Smart Structured Data

“…On the other hand, process re-engineering (PR) is an approach that can be used to improve LM and AM. It is referred to as the restructuring of the organizational process through a specific management strategy focusing on radical ground-up procedures [10]. According to the literature, PR is comprised of [21,22] the following:…”

“…These changes are building up inefficiencies, leading to strategic failure [9]. Process re-engineering in a manufacturing organization is more complex, as it requires the identification of factors that affect the process from start to end [10]. There are many factors that influence fundamental rethinking and radical redesign in bringing about improvement [8].…”

“…There are many factors that influence fundamental rethinking and radical redesign in bringing about improvement [8]. The failure factors and success factors of a process can be described as the interdependent issues that arise while implementing changes [10]. Most of manufacturing processes are reciprocal or sequential, which means that a change in one step will affect the subsequent or entire process [10,11].…”

“…The failure factors and success factors of a process can be described as the interdependent issues that arise while implementing changes [10]. Most of manufacturing processes are reciprocal or sequential, which means that a change in one step will affect the subsequent or entire process [10,11]. Before implementing changes, an organization needs to identify the interdependent issues that affect the performance or productivity of subsequent functions.…”

“…Process interdependencies can be identified through analysis of a process, and this paper discusses the process of identification of interdependencies through the integration of data-driven process re-engineering [10] and cause and effect algorithms. This paper will analyze the interdependencies caused by changing a manufacturing process and will provide a cause and effect algorithm and integrate it with data-driven process re-engineering [10]. The proposed method is termed the Khan-Hassan-Butt (KHB) method and can identify process interdependencies and optimize the process simultaneously.…”