On the Development of an Automated Adaptive Polishing System: A Review of the Conventional Processes and Trends

On the Development of an Automated Adaptive Polishing System: A Review of the Conventional Processes and Trends

Amir Hossein Baraati, Daniel Gil Afonso, Ricardo Guincho
DOI: 10.4018/IJSEIMS.313668
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Abstract

The emerge of Industrial 4.0 revolution and influences to production, information, and communication technologies have made manufacturers capable of reaching higher performance in the last decade. Making smart operations has been set as a top strategy of manufacturing societies, and machinery industry as an integral part of production has been highlighted develop. Aerospace, automotive, metals, glass, and plastics industries have been pioneers to improve, optimize, and develop automated polishing as a final operation of surface finishing process considering of KPIs: quality, time, cost, and safety. In this review, after mentioning the state of the art of last relevant papers, some clues for future research will be presented.
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1. Introduction

The mechanical surface of a work piece has been defined as the set of features in a work piece which separate the entire work piece to the surrounding medium (Blunt, 2003). The development of methods to improve a surface quality, as well as measuring it, have great importance by a number of reasons: prevention of mechanical failures in parts related to surface defects (Blunt, 2003; Polishing of UDDEHOLM mould steel, 2016); improvement of part contact in assemblies; reduce the risk of corrosion (Polishing of UDDEHOLM mould steel, 2016); possibility of performing surface treatment (Kenton, 2009); component performance (e.g. light reflection and refraction, matter adhesion, molded material ejection) (Polishing of UDDEHOLM mould steel, 2016); aesthetics reasons.

Manufacturing processes are improving, being able to reach better surface finishing economically in primary operations. Coating technologies, also known as positive or additive finishing operations, are also improving, therefore potentially replacing some negative or subtractive surface finishing. However, the need for mechanical finishing operations is still, and will be, essential to reach the increasingly demanding part quality and performance (Kenton, 2009).

There have been improvements in the mechanical finishing technology, particularly in the development of new abrasives (Nizankowsk, 2017). Nevertheless, surface finishing operations, particularly polishing, are still very time consuming skilled manual labor operations (Rebeggiani & Rosn, 2011). This means the operation is closer to a craft than a reliable production process, as it depends on individual polishers ability. Further, while skilled human operators have the advantages of quickly adapt to changes, to be flexible, and learn from mistakes, it takes a long time to train new operators and the working environment is unhealthy (Health and S. Executive, 2000; Kenton, 2009). It is therefore of great interest within industry to start to use automated polishing techniques to overcome the mentioned drawbacks, as well as improving the operators work conditions (Rebeggiani & Rosn, 2011).

In order to study and develop robust autonomous polishing systems, it is crucial to deeply understand the manual process. The final surface result, as well and intermediate steps, depends on the used tool paths, contact pressures, choice of carrier/abrasives, number of steps and process time. These factors must be selected not only to lead to the goal finish, but also to prevent possible polishing issues as orange peel or pitting (Polishing of UDDEHOLM mould steel, 2016). However, the same final result is achievable using different strategies, making it difficult to establish well defined process guidelines (Rebeggiani & Rosn, 2011).

Figure 1.

Surface Roughness

IJSEIMS.313668.f01

Nevertheless, some studies have been made towards the automation of polishing operations. Efforts include the use of robots with conventional manual polishing tools (Rebeggiani & Rosn, 2011), laser assisted methods (Ukar et al., 2010), chemical mechanical methods (Ahn et al., 2004) and fluid jet and bonnet polishing.

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