Abstract
Integrated reliability is one of the most critical components of physical asset management to foster a competitive advantage, particularly in a Volatile, Uncertain, Complex, and Ambiguous (VUCA) environment. The inherent reliability of physical assets relies on the intended equipment utilization within the specified design envelope, prescribed maintenance tactics, and at times specified maintenance intervals. Thus, maintenance management remains one of the key components to achieving equipment reliability, predominantly when such equipment is subjected to a high-production environment. Yet, maintenance management remains a challenge particularly when the intended equipment is subjected to a complex and high-production environment.
The extant literature outlined complex and dynamic systems in maintenance management as one of the challenges mainly in maintenance work management. Furthermore, the challenges in maintenance management are impacted by embedded subsystems such as Supply Chain Management (SCM), cost of maintenance (output function of financial management), production management, and Human Resources Management (HRM). The extant literature further highlights that maintenance and production practitioners often take irrational decisions driven by high levels of stress and emotions when the entire system is performing poorly. Scholars outlined different maintenance strategies and the selection thereof with little on integrated reliability management using the 4IR systems approach. Thus, integrated reliability complexity and its dynamic behavior are under-researched.
This research study integrates a system dynamic modeling and the implementation of the 4IR technologies to model an integrated reliability management system, thereby using a 4IR systems approach with specified mathematical equations. A 4IR systems approach in modeling integrated reliability management is aimed at closing the gap in the extant literature. The complex phenomenon of how maintenance management and its casual effects on internal production measures in the 4IR is modeled conceptually using systems thinking and simulated quantitatively using system dynamics simulations. Conceptualization is formulated using process mapping and the causal loop diagram thereby offering a digital maintenance work management decision-making process flow...