This paper deals with the prediction of surface roughness in manufacturing polycarbonate
(PC) by applying Bayesian optimization for machine learning models. The input variables of …

The requirement of cost-effective and ecological production systems is crucial in the
competitive market. In this regard, the focus is shifted towards sustainable and cleaner …

In this paper, an ensemble learning method, in the form of extreme gradient boosting
(XGBoost) algorithm is adopted as an effective predictive tool for envisaging values of …

In this article, the adaptive neuro-based fuzzy inference system (ANFIS) model is developed
to estimate the surface roughness (Ra) and tool vibrations (Acc) of AA6013 aluminum alloy …

With the advancements in IIoT tools and applications, real-time monitoring systems with
remote access capabilities are gaining great interest. The use of these instruments in …

The machinability of high-performance materials such as superalloys, composites, and
hardened steel has been a big challenge due to their mechanical, physical, and chemical …

All manufacturing engineers are faced with a lot of difficulties and high expenses associated
with grinding processes of AZ61. For that reason, manufacturing engineers waste a lot of …

Biocomposites are increasingly being applied in the automotive industry. For assembly
purpose, drilling process is often performed in these biocomposites parts to produce holes …

The control of surface roughness is of great significance for measuring the quality
characteristics of cold-rolled steel strip. At present, the conventional method is used to …

With the fourth industrial revolution manufacturing industry faces new challenges. Small
batches of personalized parts, where the geometry changes per part, must be produced in …