The shift team formation problem in multi-shift manufacturing operations

This paper addresses the problem of assigning operators to teams that work in single-, two-, or three-day shift systems. The problem was motivated by, and illustrated with a case situation encountered in Dutch manufacturing industry. The problem addressed forms an extension of cell formation problems which are currently in the phase of addressing labor-related issues in cell design. A generalized goal problem formulation is presented to address multiple, conflicting objectives covering cross-training of workers, ensuring adequate levels of labor flexibility and minimizing labor-related costs. The proposed solution procedure consists of two phases. In the first phase, shift systems, in which applicable machines and the sizes of each shift team are identified. The next phase deals with assignment of operators to various teams and identification of specific cross-training needs for various workers. This phase involves the use of interactive goal programming. The methodology is illustrated by details from the case situation as well as a numerical example.

Flexible automation investments: A problem formulation and solution procedure

In this paper, a multi-period replacement model, based on a mixed integer nonlinear programming formulation, is developed for flexible automation investments. The model takes into account the costs, benefits and effective utilization of several types of flexibility. The decision variables pertain to the selection and optimal implementation sequence for new, CNC modules, the replacement schedule for current equipment and the aggregate production plans for transition and subsequent periods in the planning horizon. The objective function maximized the present worth of the cash flows over the planning horizon. A two-level, exact solution method is also developed, utilizing dynamic programming methodology for the higher level sub-problem and mixed integer-linear programming for the lower level sub-problem.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31128/1/0000025.pd

LIM modeling of chemical reactions in spatially and temporally developing shear flows

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76535/1/AIAA-1994-870-916.pd

LIM Simulations of Mixing and Chemical Reaction in Gas Reburning Applications

Achieving high NOx removal efficiency with gas reburning in any given installation requires tailoring the gas injection and mixing scheme to the distributions of temperature and NOx within the furnace. The injection scheme must also be robust enough to accommodate changes in these distributions under varying furnace load conditions. These considerations suggest that advanced modeling of the reburn gas injeclion and mixing can greatly assist effective implementation of reburn technology in most installations. Results are presented from local integral moment (LIM) simulations of gas injection and mixing for reburning applications. The LIM approach is fundamentally different from classical turbulence models. It uses the fact that molecular mixing processes in turbulent flows are concentrated on universal, self-similar, small-scale structures. The model incorporates this through a local parabolization of the complete time-dependent governing transport equations on the time-evolving material surface on which gradients are concentrated. This leads to a closed set of equation governing the local integral moments along the layer-normal direction at each point on the surface, effectively transforming the original partial differential equations to a set of ordinary differential equations that can be solved on a time-evolving surface. Results from validalion cases indicate that LIM simulations can provide accurate insights into the complex now and mixing processes that are essential to successfully implementing gas reburn in any given installation

Would a risk-averse newsvendor order less at a higher selling price?

We model a risk-averse newsvendor's decision-making behavior with some commonly used classes of utility functions within the expected utility theory (EUT) framework. Under fairly general conditions of EUT, we show that a risk-averse newsvendor will order less than an arbitrarily small quantity as selling price gets larger if price is higher than a threshold value, i.e., the optimal order quantity decreases as the selling price increases.Expected utility theory Risk aversion Newsvendor model