Socio-Inspired Optimization Methods for Advanced Manufacturing Processes

Inhaltsverzeichnis

1. Frontmatter

2. Chapter 1. Introduction to Advanced Manufacturing Processes and Optimization Methodologies

   Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni

   Abstract

   Manufacturing can be defined as the application of mechanical, physical, and chemical processes to convert the geometry, properties, and/or shape of raw material into finished parts or products. This includes all intermediate processes required for the production and integration of the final product. Manufacturing involves interrelated activities which include product design, material selection, production process planning, production, quality assurance, management and marketing of products.

3. Chapter 2. A Brief Review of Socio-inspired Metaheuristics

   Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni

   Abstract

   There are several deterministic and approximation algorithms proposed so far. As the problem complexity grows the approximation algorithms have proven to be computationally cheaper as compared to the earlier ones. The approximation algorithms could be classified as bio-inspired algorithms, swarm-based algorithms and physical & chemical based algorithms. The notable bio-inspired algorithms are Genetic Algorithms, Differential Evolution, Artificial Immune System, etc.

4. Chapter 3. Multi Cohort Intelligence Algorithm

   Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni

   Abstract

   Multi-Cohort Intelligence (Multi-CI) algorithm has been proposed by Shastri and Kulkarni in [14]. The algorithm implements intra-group and inter-group learning mechanisms. It focuses on the interaction amongst different cohorts. The performance of the algorithm was validated by solving 75 unconstrained test problems with dimensions up to 30.

5. Chapter 4. Optimization of Electric Discharge Machining (EDM)

   Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni

   Abstract

   Electric Discharge Machining (EDM) is an electro-thermal, Non-Traditional Machining (NTM) process in which electrical energy is used to generate spark between tool & workpiece and thus material is removed. EDM is mainly used to machine high strength temperature resistant materials and alloys with intricate geometries and is a quite popular NTM process in the machining industry.

6. Chapter 5. Optimization of Abrasive Water Jet Machining (AWJM)

   Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni

   Abstract

   Abrasive Water Jet Machining (AWJM) is an advanced version of Abrasive Jet Machining (AWJ) which employs water as the carrier medium for abrasive particles. The AWJM process can machine complex shapes and importantly, doesn’t generate heat concentrated zones. Work piece thickness, nozzle diameter, standoff distance and traverse speed are the typical process parameters/variables for AWJM. Kerf taper angle and surface roughness are performance responses as they indicate the geometry and surface finish of machined component, respectively.

7. Chapter 6. Optimization of Micro Milling Process

   Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni

   Abstract

   Micro-Milling refers to a basic end-milling process using tools up to 1 mm in diameter. The geometry that can be produced by micro-end-milling is more flexible than those produced by lithography and other traditional micro manufacturing techniques. Furthermore, a wide range of materials could be processed using micro end milling. This chapter is based on the optimization of process parameters of micro milling performed on polymethyl methacrylate (PMMA) workpiece.

8. Chapter 7. Optimization of Micro Drilling Process

   Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni

   Abstract

   Mechanical micro-drilling is one of the most widely used methods among several micro-hole making methods because of its least dependency on the material properties. Various factors such as tool diameter, spindle speed, tool helix angle, twist angle and feed rate determine the hole quality, and thus, they have to be chosen very carefully. Controlling burr formation in micro holes is significant as it causes deterioration of surface quality which reduces product durability and precision, assembly problems, wear and tear on the surface, etc.

9. Chapter 8. Optimization of Micro Drilling of CFRP Composites for Aerospace Applications

   Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni

   Abstract

   In this chapter, variations of Cohort Intelligence (CI) algorithm have been applied for the minimization of cutting forces in \({\text{x}},\;{\text{y }}\;{\text{and }}\;{\text{z }}\) directions induced in micro drilling of carbon fiber reinforced plastic (CFPR) composite materials for aerospace applications.

10. Chapter 9. Optimization of Micro-turning Process

    Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni

    Abstract

    The micro-turning processes have received a significant attention in the production of micro components with a diversity of materials including brass, aluminium, stainless steel, etc. Cutting speed, feed and depth of cut are the general process parameters/variables for micro turning process and surface roughness, flank wear, MRR, machining time are the typical process responses.

11. Backmatter