Hierarchical modelling framework for machine tool energy optimization

Multi-objective optimization of green technology thermal drilling process using grey-fuzzy logic method

“…Fuzzy Analytic Hierarchical Network Process were implemented to reduce the vagueness and complexity presented in the green technology selection process (Promentilla et al, 2018). Hierarchical optimization drive a combination of a systematic modelling together with an efficient optimization model on the machine tools that facilitate solving two main goals: reducing the processing time and power consumption (Wójcicki, Bianchi, & Tolio, 2018). To reduce the generation of waste and the consumption of resources was established a bi-level fuzzy algorithm for a particular case of nuclear power freshwater and the wastewater treatment (Aviso, Tan, Culaba, & Cruz, 2010;Tan, Aviso, Cruz, & Culaba, 2011).…”

Cross-level model of a transfer machine energy demand using a two-machine generalized threshold representation

“…This approach was formalized (Wójcicki et al, 2018a) for the machine level side, using a hierarchical tree of MET functions for all major tasks executed by a machine tool. The final, top-level, function is a compact, Pareto-optimal, representation of the relationship between machining cycle-time and minimum energy-per-part for a MT in isolation.…”

“…It reproduces the Minimum Energy-Time function (MET function), which, in a compact form, retains the outcomes of machine level process optimization. This article relies on the work conducted by Wójcicki et al (2018a), introducing a framework for machine level modelling during system-level optimization.…”

“…Tool life estimation is performed only if, for a specific workpiece geometrical feature, varying cutting parameters are used, to modify processing rate along the MET. The MET representation includes this parameters information in the machine level hierarchical tree (Wójcicki et al, 2018a). The tooling cost of features is calculated, as a function of the processing rate, using Taylor's formula:…”

“…Each machining cycle is described as a Pareto-optimal set of energy per partcycle time pairs, which represent a range of locally optimal setups for the machine, from the point of view of energy demand and processing rate. This work is a continuation of a study by (Wójcicki et al, 2018a), which focused on the derivation of machine level Pareto front for a single processing unit in isolation, for a given job. In this paper we introduce the inter-level link, demonstrating it on a two machines system, proposing an energy saving policy.…”