Competitive pressures and technological improvements are leading many firms to consider centralized information systems to manage inventories and schedule production. We propose a simple model to explore the potential benefits of such coordination. The model represents two products competing for a single production facility. Simple Markovian behavior is assumed throughout. The key step in the analysis is the explicit solution of a queueing model with a novel priority discipline: Serve a customer from the class having the largest number of customers in the system.

Borehole transient electromagnetic (TEM) techniques have been proven to be efficient for nondestructive evaluations (NDEs) of metal casings using eddy-current properties. However, physical limitations and bad borehole conditions restrict the use of eddy-current sensors, which makes downhole casing inspections very different from those of conventional NDE systems. In this paper, we present a uniform linear multi-coil array-based borehole TEM system for NDEs of downhole casings. On the basis of the borehole TEM signal model, a numerical multi-coil array approach using the Gauss–Legendre quadrature is derived. The TEM response can be divided into two independent parts related to the transmitting-receiving distance (TRD) and the observation time and casing thickness. Using this property, the signal received by the multi-coil array is weighted to cancel the influence of the TRDs of the different array elements to obtain the optimal response according to the linearly constrained minimum variance criterion, which can be shown to be identical to that of achieving the maximum signal-to-noise ratio. The effectiveness of the proposed method was verified by applying the uniform linear multi-coil array to a borehole TEM system for NDEs of oil-well casings. Field experiments were conducted, and the results demonstrate the effectiveness of the proposed method.

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With the growth of environmental awareness, remanufacturing and sustainable manufacturing have become hot issues. Disassembly is the first step and critical activity in remanufacturing. Traditional disassembly sequence planning (DSP) focusses on sequential disassembly. However, it is inefficient for complicated products because only one manipulator is employed to execute disassembly operations. Thus, this work focusses on parallel DSP (PDSP) and proposes a selective parallel disassembly sequence planning (SPDSP) methodology, which performs disassembly compared to sequential DSP and PDSP. In this paper, a mathematical model is used to describe the constraint and precedence relationships, and a parallel sequence model is designed for parallel disassembly. A novel hybrid genetic algorithm (NHGA) based-multi-objective model of SPDSP is proposed for optimisation. In this model, two indicators are integrated: disassembly time (including basic disassembly time, tool exchange time and direction change time) and disassembly costs. A transmission box is used as an instance, and a comparison with conventional genetic algorithm (GA), simulated annealing (SA) and tabu search (TS) is made to validate the practicality of the proposed methodology.