Simulation-based support tool for operator performance in batch manufacturing

In industry, the workload and utilization of shop floor operators is often misunderstood. In this paper, we will present several real case studies, using Discrete Event Simulation (DES) models, which allow us to better understand operators in a batch manufacturing environment. The first study investigates labour in a machining plant consisting of multiple identical CNC machines that batch produce parts. The second study investigates labour in an eight station, gravity die casting rotary table. The results from these studies have shown that there can be potential improvements made by the production planners in the current labour configuration. In the first case study, a matrix is produced that estimates what the operator's utilization levels will be for various configurations. From this, the preferred operator to machine ratio over a range of cycle times is presented. In the second study, the results have shown that by reducing the casting cycle time, the operator would be overloaded. A discrete event simulation of these two cases highlighted areas that were misunderstood by plant management, and provided them with a useful decision support tool for production planning.

Regional trade agreements : performance evaluation and research agenda

This paper proposes a broad model for key success factors in Regional Trade Agreements (RTAs). Current literature is relatively limited in its focus on largely economic consequences of RTAs and the externalities are mostly ignored. This model incorporates five predictor dimensions forming the character of a RTA as follows: (1) Economic, (2) Socio-Cultural, (3) Negotiation, (4) Country Objectives and (5) Review process. It proposes a methodology for the empirical testing of the proposed model. The proposed model, potentially, facilitates the measurement of the character of a RTA and its association with various RTA objectives.

Evaluating the performance of horizontal subsurface flow constructed wetlands using natural zeolite (escott)

The objective of the present study was to assess the simultaneous removal of physiochemical parameters in moderate strength wastewater using a lab scale horizontal subsurface flow constructed wetland (HFCW) with natural zeolite as a substrate. In this study, high-density polyethylene tanks (0.36 m²) were planted with phragmites australis and scirpus maritimus and received 0.012 m³/d to 0.08 m³/d of synthetic wastewater corresponding to a HLR of 0.035 to 0.243 m/d and a COD loading rate of 0.0148 kg COD (m².d)^-1 to 0.026 kg COD (m².d)^-1. The HFCW was subjected to three hydraulic retention times (HRT) for 4, 3 and 2 days respectively. Averaged data reported coincided with the plant age (4 to 55 weeks) and covered the entire cold season and early part of the hot season. Based on the 55 weeks of operation, the HFCW unit with zeolite achieved significantly higher removal for COD (85 to 88%), TN (54 to 96%), NH₄-N (50 to 99%) and TSS (91 to 96%) respectively at all HRT. This system was proved to be tolerant to high organic loadings and nutrients, suggesting these substrates as viable options for biological treatment of wastewater.

Treatment: six public artworks at the western treatment plant

This large scale curated Public Art project responds to the landscape, histories and technologies at Melbourne Water's Western Treatment Plant, Werribee. TREATMENT, with curator David Cross, associate curator Cameron Bishop, and six leading Australian artists - Bindi Cole Chocka, Megan Evans, Shane McGrath, Catherine Bell, Techa Noble and Spiros Panigirakis - have been supported to research the site and create artworks experienced by bus, across the plant. The artists have been commissioned to develop projects at a variety of sites. Sensory, technological, community and historical engagement are key aspects of this high profile project.

Blind column selection protocol for two-dimensional high performance liquid chromatography

The selection of two orthogonal columns for two-dimensional high performance liquid chromatography (LC×LC) separation of natural product extracts can be a labour intensive and time consuming process and in many cases is an entirely trial-and-error approach. This paper introduces a blind optimisation method for column selection of a black box of constituent components. A data processing pipeline, created in the open source application OpenMS®, was developed to map the components within the mixture of equal mass across a library of HPLC columns; LC×LC separation space utilisation was compared by measuring the fractional surface coverage, fcoverage. It was found that for a test mixture from an opium poppy (Papaver somniferum) extract, the combination of diphenyl and C18 stationary phases provided a predicted fcoverage of 0.48 and was matched with an actual usage of 0.43. OpenMS®, in conjunction with algorithms designed in house, have allowed for a significantly quicker selection of two orthogonal columns, which have been optimised for a LC×LC separation of crude extractions of plant material.