Applications of the Jameson cell at the head of base metal flotation circuits

The Jameson Cell is a high intensity flotation device, which utilises induced air from the atmosphere. It was developed jointly by Mount Isa Mines and Professor Graeme Jameson of the University of Newcastle in the 1980s. It is proven to generate fine bubbles, in the order of 300 to 500 µm, in a high intensity, high shear and compact zone contained in the downcomer. This aerated mixture exits the downcomer into the pulp zone, which is the quiescent mineral and gangue separation zone. A number of Australian base metal flotation circuits feature a reverse flotation stage at the head of the circuit. Testwork and plant operating data has shown that the use of a Jameson Cell in the prefloat cleaner application has further improved prefloat gangue recovery and selectivity. Operation of a Jameson Cell in a carbonaceous/pyrite prefloat cleaner duty at the Mt Isa copper concentrator increased copper recovery and reduced pyrite in the copper concentrate. Testwork at Zinifex Century Zinc Mine showed a decrease in zinc losses by the utilisation of Jameson Cell prefloat cleaner. Appraisal of a Jameson Cell in a scalping role within the Mt Isa Copper Concentrator indicated significant benefits could be achieved.

Optimization of PCB component placements for the collect-and-place machines

This paper presents two hybrid genetic algorithms (HGAs) to optimize the component placement operation for the collect-and-place machines in printed circuit board (PCB) assembly. The component placement problem is to optimize (i) the assignment of components to a movable revolver head or assembly tour, (ii) the sequence of component placements on a stationary PCB in each tour, and (iii) the arrangement of component types to stationary feeders simultaneously. The objective of the problem is to minimize the total traveling time spent by the revolver head for assembling all components on the PCB. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method, the nearest neighbor heuristic, and the neighborhood frequency heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different population sizes. It is proved that the performance of HGA2 is superior to HGA1 in terms of the total assembly time.

Optimal production planning for PCB assembly

It is indisputable that printed circuit boards (PCBs) play a vital role in our daily lives. With the ever-increasing applications of PCBs, one of the crucial ways to increase a PCB manufacturer’s competitiveness in terms of operation efficiency is to minimize the production time so that the products can be introduced to the market sooner. Optimal Production Planning for PCB Assembly is the first book to focus on the optimization of the PCB assembly lines’ efficiency. This is done by: • integrating the component sequencing and the feeder arrangement problems together for both the pick-and-place machine and the chip shooter machine; • constructing mathematical models and developing an efficient and effective heuristic solution approach for the integrated problems for both types of placement machines, the line assignment problem, and the component allocation problem; and • developing a prototype of the PCB assembly planning system. The techniques proposed in Optimal Production Planning for PCB Assembly will enable process planners in the electronics manufacturing industry to improve the assembly line’s efficiency in their companies. Graduate students in operations research can familiarise themselves with the techniques and the applications of mathematical modeling after reading this advanced introduction to optimal production planning for PCB assembly.