A System Dynamic-based Archetype for Capital Leasing of Industrial Robots Academic Article in Scopus uri icon

abstract

  • © 2022 PICMET.Over the past forty years, leasing has gained ground as a competitive alternative to test and possibly absorb new technology, especially in light of the increasing costs of technology and capital. Additionally, leasing has allowed companies to mitigate financial risk associated with new equipment acquisition. Given these benefits of leasing, its popularity as a technology acquisition alternative can be expected to grow further. Unfortunately, despite the existence of a large body of extant literature on the technical aspects of automation, little is known about the economic effects of industrial robot leasing in manufacturing organizations. Given such information scarcity, both in literature and data published by companies, simulation presents itself as a viable solution to study the economic effects. In fact, simulation using System Dynamics (SD) has been demonstrated to be robust and reliable in the face of information scarcity. Unlike operating leasing, for which SD-based archetypes have previously been published, no such SD-archetype exists for capital leasing because of its complexity. To illustrate a basic difference, an operating lease is recorded as an expense on the income sheet, whereas the upfront cost or the entire leasing value of a capital lease is recorded as an asset on the balance sheet. To address this lacuna in literature, our work presents an SD-archetype to model the economic effects of capital leasing of industrial robots on a manufacturing facility. The development of an SD archetype is the main contribution of this work.

publication date

  • January 1, 2022