During the Classical Period (300 BC-400 AD), the Indian Ocean emerged as one of the largest hubs of ancient international trade. For a long period, these contacts were described from a Rome-centric point of view, looking at the connections between Rome and India. However, recent studies have demonstrated that the Roman-Indo connection was only one of the vast medium and short distance trade routes involving numerous regions and populations, exchanging goods and culture. Current archaeological investigations have demonstrated that several minor trade dynamics formed the primary connective tissue of the Indian Ocean. This study attempts to trace these mid-range connections by focusing on the transport of torpedo jars, recently found in several settlements throughout the Indian Ocean. Two archaeological sites were considered: Al Hamr al-Sharqiya 1 (Inqitat, southern Oman), and the port of Alagankulam (southern India). An analytical protocol based on thin sections analysis, SEM-EDS, XRD and GC/MS was applied to a selection of fragments from the two archaeological sites. The analytical investigation carried out on these vessels identified three different ceramic compositions, which distributed differently in the two sites, characterized by a black coating due to a similar bitumen source. The location of the production sites and comparative studies between these vessels and reference materials available in the literature enabled us to cast new light on the routes followed by the torpedo jars, from Mesopotamia to India and Oman.

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Hard turning is a profitable alternative to finish grinding. The ultimate aim of hard turning is to remove work piece material in a single cut rather than a lengthy grinding operation in order to reduce processing time, production cost, surface roughness, and setup time, and to remain competitive. In recent years, interrupted hard turning, which is the process of turning hardened parts with areas of interrupted surfaces, has also been encouraged. The process of hard turning offers many potential benefits compared to the conventional grinding operation. Additionally, tool wear, tool life, quality of surface turned, and amount of material removed are also predicted. In this analysis, 18 different machining conditions, with three different grades of polycrystalline cubic boron nitride (PCBN), cutting tool are considered. This paper describes the various characteristics in terms of component quality, tool life, tool wear, effects of individual parameters on tool life and material removal, and economics of operation. The newer solution, a hard turning operation, is performed on a lathe. In this study, the PCBN tool inserts are used with a WIDAX PT GNR 2525 M16 tool holder. The hardened material selected for hard turning is commercially available engine crank pin material.Keywords Hard turning · DOE · Material removal rate · Signal-to-noise ratio · Tool life · Validation IntroductionNormally, the hard turning operation is performed on materials having hardness values over 45 HRC in "C" Scale of hardness tester [1]. The polycrystalline cubic boron nitride (PCBN) tools used for hard turning are broadly classified as low-content T. Tamizharasan · T. Selvaraj · A. Noorul Haq (u)

Machining processes have emerged as an important requirement in product design concepts, manufacturing applications, and the overall functional aspects of the product. For machining a component, it is important to understand the characteristics of work material in order to choose the appropriate cutting tool and to fix a set of machining parameters to achieve optimum output. This article presents the details of experiments conducted for machining Inconel 718, by turning process, with two different coated carbide tool inserts (KC5525 and HK150), with an objective of optimizing the process. Furthermore, four different analytical models were developed, validated, and compared to exhibit their performance in establishing the input–output relationship. A set of input machining parameters were chosen to yield a higher material removal rate (MRR), coupled with a moderate surface finish. Experimental data were generated for the chosen set of input parameters and the resultant output parameter and the machining performance of the two tool inserts was compared. With the above experimental data, Analytical models were developed, using genetic programming (GP), artificial neural networks (ANN), adaptive neuro‐fuzzy inference system (ANFIS) and the mathematical regression models with an objective of minimizing the surface roughness while turning Inconel‐718. The effect of machining parameters on the surface roughness was evaluated and the optimum machining condition for minimizing the surface roughness was determined; further the order of influencing input parameters was brought out. Prediction accuracy of the four models was established and the above models were validated, using the different set of experimental data. Comparison of performance of the four models is discussed, extent of prediction accuracy of each model is brought out and the advantages, disadvantages, and limitations of the four models are outlined in this article. This shall be a reference to the machinists to choose appropriate cutting parameters to meet the surface finish requirements demanded by the product designers.

Purpose – This paper aims to apply Value Stream Mapping (VSM) for enabling leanness in an Indian automotive components manufacturing organization. Design/methodology/approach – The study was initiated with the selection of product line, construction of current state map, identification of various wastes and the development of future state map. The improvement proposals were subjected to implementation and performance measures were quantified. Findings – The expected outcomes of the study include the quantification of wastes, improvement in manpower productivity, quality improvement and throughput time reduction. Research limitations/implications – The implementation study has been conducted in only one manufacturing organization. The experiences gained by the conduct of this implementation study are feasible and deployable in similar manufacturing organizations. Practical implications – The results of the study indicated that significant improvement in lean characteristics is possible as a result of the implementation of VSM. Originality/value – The paper reports a real-time study conducted in an automotive components manufacturing organization. Hence, the contributions are original.