A labelling system and automation comparison index for industry 4.0 system

Abstract

Purpose This paper aims to put forward a labelling system capable of reflecting the level of different Industry 4.0 (I4.0)features present in a manufacturing system and further propose a comparative index to collectively estimate and compare the system automation level. Design/methodology/approach Data for the empirical study were collected from interactions with the practising managers and experts. A relationship among the six I4.0 features is developed with fuzzy cognitive maps. Findings The paper proposed a simple and easy-to-understand labelling system for I4.0 systems, which indicates the automation level in each of six dimensions of any manufacturing system. The system is further strengthened by a proposed automation comparative index (ACI), which collectively reflects the automation level on a scale of “0” to “1”. Thus, the labelling system and parameter could help in comparing the level of automation in the manufacturing system and further decision-making. Research limitations/implications Only seven industrial sectors are illustrated in the paper, but the proposed concept of the classification scheme and ACI find their applicability on a large spectrum of industries; thus, the concept can be extended to other industrial sectors. Furthermore, a threshold value of ACI is a differentiator between a I4.0 and other automated systems. Both aspects have the scope of further work. Practical implications The way and pace by which the industrial world takes forward the concept of I4.0, soon it will need a labelling system and a parameter to assess the automation level of any automated system. The scheme assesses the automation level present in a manufacturing system. It will also estimate the level of the presence of each of all six attributes of an I4.0 system. Both labelling system and ACI will be the practical tools in the hands of the practising managers to help compare, identify the thrust areas and make decisions accordingly. Originality/value To the best of the authors’ knowledge, this is the first study of its kind that proposed the labelling system and automation comparison index for I4.0 systems.

3D printing towards implementing Industry 4.0: sustainability aspects, barriers and challenges

“…As a result of this shift, manufacturing and all the other related processes became intricate, and they are needed to be made sustainable to make the operation of these machines simple, efficacious and diligent (Qin et al , 2016). Lesser profit margins, different customer demands, more competition and fast fabrication of customized products forced the manufacturers to resort to more advanced methods of manufacturing to produce low-cost products with improved quality and high levels of precision (Kumar et al , 2021).…”

Development of an industry 4.0 transformability index for manufacturing systems

“…Different aspects related to the I4.0 regime, such as maturity models (Caiado et al , 2021), sustainability functions (Ghobakhloo, 2020), sustainability aspects (Bai et al , 2020; Machado et al , 2019; Müller et al , 2018), relation/integration with other industrial practices (Davis et al , 2020; Javaid et al , 2021; Tortorella et al , 2019), supply chain (Hofmann et al , 2019; Tiwari, 2020), possible impacts (Kumar et al , 2020b; Ulusoy et al , 2021), facility layout (Ficko et al , 2021), robotic collaborations (Dobra and Dhir, 2020; Goel and Gupta, 2020; Inkulu, 2021), human factors and ergonomic analysis (Laudante, 2017; Neumann et al , 2021) and others are also highlighted in the literature. Recently (Kumar et al , 2021c) proposed a labeling system and comparative index for comparing the automation levels in two or more I4.0 systems. Schlechtendahl et al (2015) rightly remarked that transforming the existing stock of production systems into I4.0 compatible units would be a viable option to adopt the concept of smart factories.…”