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C103 Nb alloy shows the good consistent microstructure that leads to better controlled properties of the material such as high strength, stress resistance, fabricability, and high temperature resistance. C103 Nb alloy shows the unique properties for challenging the aerospace, orbital rocket nozzles or chambers, and jet engine applications but they are costly and difficult to machine through traditional technique like single point cutting operation. Laser assisted heating plays a significant role in machining process due to easy and to develop very high intense heat energy in a precise region The generated energy leads to soften sample and smooth machining surfaces with crack free and superior quality. The present work deals with the influence of cutting parameters (laser power (LP) and depth of cut (DoC)) on the responses (surface roughness and cutting force (CF)) of C103 Nb alloy through laser assisted machining process at constant feed rate (0.02 mm/rev) and constant cutting speed (500 rpm). Based on the experimental results, LP shown the significance influence on surface roughness, CFs and decreases with increase of LP and increases with increase of DoC. [ABSTRACT FROM AUTHOR]

Machining of Nitinol alloy is complicated by the traditional process due to severe strain hardening and low thermal conductivity, which prompts high tool wear and indigent surface quality. Wire Electro Discharge Machining (WEDM) has been most commonly used for machining Nitinol alloy. In this paper, the effect of input attributes such as pulse on time (Ton), pulse off time (Toff), peak current (Ipeak) and voltage (V) on metal removal rate (MRR) and surface roughness (SR) during WEDM of Nitinol alloy have been investigated. Experiments were conducted according to central composite design (CCD) of response surface methodology (RSM). Analysis of variance (ANOVA) was used for studying the effect of input attributes and their interactions. It is perceived that at smaller values, Ton and Ipeak are more significant attributes for improving the MRR and surface finish. The optimum conditions are obtained for minimising surface roughness and maximising MRR using RSM and Desirability analysis. Confirmation test was conducted with optimum input attributes where the estimated values of the output attributes were contrasted with the experimental results. It was established that the experimental and the estimated values are in very close agreement. [ABSTRACT FROM AUTHOR]

Byline: Sandeep Dulluri, V. Mahesh, C.S.P. Rao The increasing importance of make-to-order manufacturing, inventory reduction and resource optimisation have placed further emphasis on the growing role of scheduling in the current global business environment. Often there has been a problem of applying the mathematically rich concepts of scheduling theory to solve the real-time industrial problems – in particular the problem of job-shop scheduling. In this context, in our current work, we develop a priority-based heuristic for minimising the makespan for a turbine manufacturing industry. This heuristic gives the optimal schedule based on the dynamic priorities of the customer work orders. We also propose bounds for makespan in job-shop scheduling environment. There are a host of issues addressed by the job shop scheduling system, like resource break-down, reentrance of the jobs on the resources that are already visited by the job. Our research helps in connecting the academic theory with real-time industrial scheduling problem to get better quality results.

Byline: Ch. Srinivas, C.S.P. Rao In this paper, we develop an inventory model where the replenishment lead time is assumed to be dependent because at the time of contract with a manufacturer retailer may intend to reduce the lead time for which he pay an additional cost to accomplish the increased production rate. We provide a solution procedure to obtain the efficient ordering strategy in Hill's inventory model in particularly Consignment Stock (CS) policy of Supply Chain Management (SCM) for a single vendor-single buyer under the stochastic nature. The lead time of CS strategy has been controlled to minimise Joint Total Expected Cost (JTEC) and simultaneously optimised other decision variables such as quantity transported, lead time, the number of transport operations and delay deliveries under stochastic environment so as to gain a competitive advantage in the business strategy. Numerical examples are presented to illustrate the solution procedure.