Journal of Advanced Manufacturing Systems

Maintaining relationships with suppliers has become a critical strategic management issue to business. As a consequence, the tasks of evaluating and selecting suppliers are essential, given that companies delegate part of their business to partners. The main purpose of these tasks is to identify suppliers with the highest potential for meeting a buyer’s needs consistently and at an acceptable overall performance. However these tasks are complex since they involve a variety of conflicting criteria, which makes the problem one that can be tackled by an multicriteria decision aid (MCDA) approach. Moreover, companies have suppliers whose features and performance are different and buyers need to decide at each level how they may best collaborate with each type of supplier. Many papers in the literature have addressed this situation involving supplier selection; nevertheless, most of them present methods to solve ranking and choice problems. The objective of this paper is to propose a model for the strategic management of suppliers which uses the ELECTRE TRI method to sort suppliers into classes of collaboration. Therefore, by using this model it is possible for companies to do so in order to define the most appropriate strategies to adopt for each category.

To use regenerative brake and mechanical brake co-operatively to maintain the constant speed and the braking energy can be regenerated as much as possible when vehicles travel downhill, the mathematical model of the braking system is established, and the adaptive model predictive control method is adopted to control the speed of vehicles. The recursive least square algorithm with the forgetting factor is used to identify the road gradient online. And then the control results of the adaptive model predictive control are compared with the results of PID control, simulation results show that the robustness and the stability of the adaptive model predictive control method are better. The speed can be maintained basic stability with the coordinated use of the regenerative braking and the mechanical braking. Meanwhile, the braking energy can be regenerated as much as possible as the regenerative braking system can be used as much as possible. Moreover, as the charge acceptance ability of the battery is restricted, the brake mode switching model is designed. The braking mode can be switched between the electro-mechanical braking system and mechanical braking system according to the SOC of the batteries.

This paper presents a case study on comparison of Design of Experiments (DOE) via traditional and Taguchi methods in terms of efficiency. First, a three-level, four-parameter, full factorial DOE was conducted for finding the effects of machining parameters on the surface roughness (arithmetic average) of parts produced by turning operation. The results were analyzed applying average response, Taguchi’s $S$/$N$ ratio, and Pareto ANOVA. Subsequently, the same data was analyzed applying Taguchi’s L9 orthogonal array. The comparison of two results revealed that despite an 88.9% savings of experimental runs with the Taguchi method, both methods produced similar results.

In this paper, endeavor has been made to design and analyze different Y-type micromixers by characterizing the mixing and flow behavior in ultra-low Reynolds number region. The effects of different geometric and flow parameters on the mixing and pressure drop are studied through computational fluid dynamics (CFD) simulations using COMSOL Multiphysics software. The parameters investigated are obstacle geometry, obstacle arrangement, obstacle depth, aspect ratio (AR), entrance angle ($E_{\theta })$, Reynolds number (Re) and obstacle packing factor (OPF). The simulation results reveal that rectangular shaped obstacles in staggered arrangement gives the best mixing. Increasing obstacle depth and OPF increases both mixing and pressure drop whereas increasing entrance angle enhances mixing but has negligible effect on pressure drop. Also both the mixing and pressure drop performance enhances with decreasing AR and lower Reynolds number gives better mixing in the lower laminar flow region.