Abstract: In recent years, environment regulation forcing
manufactures to consider recovery activity of end-of- life products
and/or return products for refurbishing, recycling,
remanufacturing/repair and disposal in supply chain management. In
this paper, a mathematical model is formulated for single product
production-inventory system considering remanufacturing/reuse of
return products and rate of return products follows a demand like
function, dependent on purchasing price and acceptance quality level.
It is useful in decision making to determine whether to go for
remanufacturing or disposal of returned products along with newly
produced products to satisfy a stationary demand. In addition, a
modified genetic algorithm approach is proposed, inspired by particle
swarm optimization method. Numerical analysis of the case study is
carried out to validate the model.
Abstract: This work presents the results of a study carried out to
determine the sliding wear behavior and its effect on the process
parameters of components manufactured by direct metal laser
sintering (DMLS). A standard procedure and specimen had been used
in the present study to find the wear behavior. Using Taguchi-s
experimental technique, an orthogonal array of modified L8 had been
developed. Sliding wear testing using pin-on-disk machine was
carried out and analysis of variance (ANOVA) technique was used to
investigate the effect of process parameters and to identify the main
process parameter that influences the properties of wear behavior on
the DMLS components. It has been found that part orientation, one
of the selected process parameter had more influence on wear as
compared to other selected process parameters.
Abstract: Supply chain consists of all stages involved, directly
or indirectly, includes all functions involved in fulfilling a customer
demand. In two stage transportation supply chain problem,
transportation costs are of a significant proportion of final product
costs. It is often crucial for successful decisions making approaches
in two stage supply chain to explicit account for non-linear
transportation costs. In this paper, deterministic demand and finite
supply of products was considered. The optimized distribution level
and the routing structure from the manufacturing plants to the
distribution centres and to the end customers is determined using
developed mathematical model and solved by proposed particle
swarm optimization based genetic algorithm. Numerical analysis of
the case study is carried out to validate the model.