P. Pitchipoo

Vellore Institute of Technology University

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S. Rajakarunakaran

Kalasalingam Academy of Research and Education

P. Venkumar

Kalasalingam Academy of Research and Education

N. Rajini

Kalasalingam Academy of Research and Education

K. Mayandi

Kalasalingam Academy of Research and Education

J.T. Winowlin Jappes

Kalasalingam Academy of Research and Education

S. Senthil Kumar

SRM Institute of Science and Technology

S. Manoharan

National Institute of Technology Tiruchirappalli

D.S. Vincent

D. Sundarrajan

Rajakarunakaran Sivaprakasam

Cooperative Institutions

Kalasalingam Academy of Research and Education

Anna University, Chennai

Yes Technologies (United States)

Vellore Institute of Technology University

Saveetha University

King Mongkut's University of Technology North Bangkok

Tirunelveli Medical College

Madurai Medical College

SRM Institute of Science and Technology

KPR Institute of Engineering and Technology

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Modelling and development of decision model for supplier selection in process industry

International Journal of Computer Aided Engineering and Technology (2011)

P. Pitchipoo P. Venkumar S. Rajakarunakaran K. Muthugurupackiam

The selection of appropriate supplier is one of the most critical decisions in the competitive business environment. In this study a decision support model has been developed for supplier selection using analytic hierarchy process by considering both qualitative and quantitative criteria. The proposed model is illustrated with a case study of an electroplating industry to demonstrate the effectiveness of this model. Through the proposed model, it is promising to effectively combine the specialised knowledge, experience and the quantitative data to select the best suppliers.

Decision model

Decision-making models

Supplier evaluation

10.1504/ijcaet.2011.042359

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Citations (2)

Subsequent welding of mild steel in the pipeline industry: mechanical, wear and microstructure characteristics

Welding International (2023)

M. Thirukumaran Shanawaz Abdul Kadar Mohamed Kalimuthu Muthuvel P. Sivasamy Muthiah Athenamilagi

In this work, an attempt was made to join MS IS2062 using a combination of gas tungsten arc welding (GTAW) and shielded metal arc welding (SMAW) processes using various welding parameters to get the best weldability. An initial scanning electron microscope study was conducted to determine the microstructure of the sample. In addition to measuring and correlating microstructures and welding parameters, mechanical properties like tensile strength and microhardness are also measured. Here, friction force (FF) and specific wear rate (SWR) were carried out to analyse the tribological behaviour of the weld joint. It was found that the weld MS IS2062 by subsequent welding achieved 15% and 5% higher yield strength and 5% and 4% harder than SMAW and GTAW. Pull-off and cracks were found in the tensile fracture image, and changes in grain boundaries have been observed in the microstructural study. The contact pressure shows the greatest influence on roughness and FF; at the same time, velocity influences the SWR, as found in the experimental results. The subsequent welding process was performed with good stabilisation by balancing between the SMAW and GTAW welding, and to obtain superior properties, we must optimise our results and choose the best possible method.

Weldability

Friction Welding

10.1080/09507116.2023.2288099

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Citations (2)

Mechanical performance of Cissus quadrangularis/polyester composite

Materials Today Communications (2015)

K. Mayandi N. Rajini P. Pitchipoo J.T. Winowlin Jappes I. Siva

Thermosetting polymer

Bast fibre

Polyester resin

10.1016/j.mtcomm.2015.08.001

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Citations (34)

Numerical Study of Drilling Parameters with Al 356 Alloy Using Bacterial Foraging Optimization

Materials science forum (2024)

P. Pitchipoo Muthiah Athi Manikandan Annamalai Jeyakumar Kadarkarai S. Rajakarunakaran

A mechanical work piece created industrially frequently contains more than one machining process. Furthermore, it is a common activity of programmers, who make this selection every time a milling and drilling operation is conducted. Tool wear and borehole quality are two essential challenges for high precision drilling procedures, with Al 356 alloy being employed in experimental planning. Drilling specifications will be assessed in this work to get optimal parameters in minimizing the influence of drilling damage on alloy using a swarm-based optimization model. The drilling parameters are optimized using the Bacterial Foraging Optimization (BFO) method, which includes three control factors: depth, feed rate, and spindle speed. Each parameter is designed in three levels, with multiple performance characteristics such as thrust force, surface roughness, and delamination factor. This investigation was carried out in order to obtain the proper optimization. The feed rate, next to the spindle speed, was discovered to be the essential element inducing lamination in drilling, with this phenomenon occurring in each diameter of the drill bit. The results reveal that the feed rate and drill type are the most important parameters influencing the drilling process, and that employing this strategy can successfully improve drilling process outcomes.

10.4028/p-6hukkb

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Citations (0)

Characterization and machining analysis of AA3003 honeycomb sandwich

Materials Today Proceedings (2020)

Rajagopal Yogeswaran P. Pitchipoo

Honeycomb

Honeycomb structure

Limiting

10.1016/j.matpr.2019.12.101

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Citations (8)

A Novel Optimization of Friction Stir Welding Process Parameters on Aluminum Alloy 6061-T6

Materials Today Proceedings (2018)

M. Gomathisankar M. Gangatharan P. Pitchipoo

Friction Stir Welding

Orthogonal array

Design of experiments

Process variable

Dwell time

10.1016/j.matpr.2018.03.025

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Citations (32)

Sustainable Characterization of Silane Treated and Untreated Psidium Guajava Stem Natural Fibers Based Automobile Brake Pads

Journal of Natural Fibers (2021)

Sundarrajan Dharmakrishnan P. Pitchipoo S. Manoharan

The present study deals with the extraction and characterization of untreated and silane-treated natural fibers from stems of Psidium guajava (Guava plants) for automobile brake pad applications. The extraction of fibers was done from the Psidium guajava plant stems by the retting process followed by silane treatment. The untreated and silane-treated Psidium guajava fibers were analyzed for chemical, physical, and crystalline properties. These fibers were used in the brake pad composite developed using conventional industrial processes and analyzed for various performance characteristics as per industrial standards. The tribological performance of the developed brake pads was measured using the Chase test following IS 2742 Part-4 of 1994or SAE J661:2012. It was found that silane-treated Psidium guajava fibers had acrystalline index of 42%, while it was 27% for untreated Psidium guajava fibers. The brake pads developed using silane-treated Psidium guajava fibers showed ahigher hardness of 99, while it was 90 for untreated Psidium guajava fibers proving better results upon the usage of silane-treated Psidium guajava fibers in brake pads. Scanning Electron Microscope studies of Chase tested brake pads that elucidated the plateau formations and back transfers.

Psidium

10.1080/15440478.2021.1958429

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Citations (13)

Development of fuzzy expert system for supplier evaluation and selection

IEEE-International Conference On Advances In Engineering, Science And Management (2012)

P. Pitchipoo P. Venkumar S. Rajakarunakaran

In present global scenario the competition among business organizations increases exponentially and hence they are forced to follow supply chain management. Customer satisfaction is the prime criteria to maintain the organization's profit in a supply chain. An important aspect of supply chain management is the supplier management. The supplier management includes supplier evaluation, selection and development. Supplier selection problem plays a significant role as strategic features in a company success. Improper evaluation and selection of potential supplier can reduce the organization supply chain performance. Supplier selection problem is a multi criteria decision problem in which both qualitative and quantitative factors are involved. In this paper a fuzzy logic expert system was developed for supplier selection in a process industry. The developed system will resemble a human judgment in correlating knowledge that represents the requirements of decision maker. This fuzzy expert system was piloted in a chemical industry and results showed that test effectiveness and efficiency was significantly improved.

Supplier relationship management

Supplier evaluation

Source

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Citations (7)

A Hierarchical Decision Support System for Supplier Selection in Process Industry

Automation and Autonomous Systems (2011)

P. Pitchipoo P. Venkumar S. Rajakarunakaran

Supplier selection is recognized as a critical decision in supply chain management in process industries. In such industries the procurement department plays an important role in reducing purchasing cost and selecting appropriate suppliers. The supplier selection problem is a multi criteria unstructured problem. Several key factors like quality, cost, delivery time and warranty etc., are commonly involved in the supplier selection decision making process. In this paper a hierarchical decision support system was developed for selecting the best supplier by using analytic hierarchy process model. This model was illustrated with a case study in a cement industry.

Supplier relationship management

Supplier evaluation

Warranty

Delivery Performance

Decision model

Purchasing process

10.36039/aa112011001

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Citations (0)

Investigation of Wear and Wire Electrical Discharge Machining Characteristics of Al-Mg-MoS2 Composites Using Response Surface Method

Journal of Testing and Evaluation (2022)

S. Senthil Kumar P. Pitchipoo P. Pitchipoo T. S. Senthilkumar S. G. Ponnambalam

Abstract Aluminum metal matrix composites remain sophisticated materials with a broad series of applications because of their high strength-to-weight ratio, better resistance to wear and corrosion, improved high-temperature zone applications, and reasonable machinability. Furthermore, when manufactured through the powder metallurgy process, the tribological and machinability properties of aluminum-magnesium–based composites are found to be improved with the inclusion of molybdenum disulfide reinforcement. The response surface methodology technique was used for estimating the wear loss and coefficient of friction to study the tribological property. Also, it is employed in the wire electrical discharge machining (WEDM) technique, to predict material removal rate, surface roughness, and overcut. The projected values in both the wear and WEDM parameters are well within the minimal error value, according to the perturbation plot, and sufficient validation has been performed. The created model reveals that at 15 N, 2 m/s, 750 m, and 15 A, 90 µs, and 45 V, better tribology and WEDM characteristics are acquired.

Electrical Discharge Machining

Machinability

Powder Metallurgy

10.1520/jte20220327

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Citations (9)