Identification and design of industry 4.0 opportunities in manufacturing: Examples from mature industries to laboratory level systems

Considering the nascent application of advanced technologies in industry within the context of the new industrial revolution, we propose a methodology for identification and design (ID) of smart operations in manufacturing. The ID study considers the elements of the Industry 4.0 (I4) such as autonomous robots, advanced analytics, systems integration, high-end sensing, big data, internet of things, cloud computing and human-machine interactions. Toward achievable I4-based production, the proposed IDoI4 (ID-of-I4) approach integrates I4 fundamental elements regarding a) modelling and solution algorithms (MSA), b) information and communication technologies (ICT), c) high-performance computing (HPC), and d) mechatronics (MEC). These four groups of the I4 elements are examined in the industrial cases covering from mature industries to laboratory level systems to determine their current technological states and gaps into the I4 stage. The examples highlighted are crushed-ore stockpile level control in the mining field, resin bed cleaning timetabling in water demineralisation treatment, compositional data-driven real-time optimisation of hydrocarbon streams and diverse I4 basics in the next generation of biorefineries. In the main example, supported by a high-end sensing apparatus to measure crushed-ore stockpile levels in real-time (live inventory as a controlled variable by a target), a hybrid dynamic control prescribes (every 4 minutes) discrete positions and time-slots of the shuttle-conveyor tripper car mechatronics that creates the stockpiles. From such IDoI4 methodology, a table on the MSA, ICT, HPC and MEC ground bases summarises how such technologies are integrated to the industrial examples considering research, development and deployment in stable, demanded and highly demanded stages of the technologies into the I4 mandate.