Mineral Processing Plants Research Articles

Optimal control of mineral processing plants using constrained model predictive static programming

The model predictive static programming (MPSP) technique, which is extended recently to incorporate applicable state and control constraints, operates on the philosophy of nonlinear model predictive control (NMPC). However, it reduces the problem into a lower-dimensional problem of control variables alone, thereby enhancing computational efficiency significantly. Because of this, problems with larger dimensions and/or increased complexity can be solved using MPSP without changing the computational infrastructure. In this paper, the MPSP technique with applicable constraints is applied to two challenging control problems in the mineral processing industry: (i) a single-stage grinding mill circuit model, and (ii) a four-cell flotation circuit model. The results are compared with a conventional nonlinear MPC approach. Comparison studies show that constrained MPSP executes much faster than constrained MPC with similar/improved performance. Therefore, it can be considered a potential optimal control candidate for mineral processing plants.

Investigation of the usage of waste materials and By-Products as grinding aids in calcite grinding

Along with the increasing importance of water worldwide, it is thought that developments in fine grinding processes performed by dry grinding and using grinding aids are too essential to be ignored. Indeed, grinding chemicals in the form of pure or commercial mixtures are intensively used in mineral processing plants in dry grinding systems to micronized sizes, e.g., dry grinding of calcite to micronized sizes. This study investigated the usage of olive pomace oil (OPO) and olive waste water (OWW), waste/by-products of the olive oil industry, as grinding aids in the dry grinding of calcite to micronized sizes using a laboratory-scale stirred ball mill and compared them with pure and commercial grinding aids. The test results were evaluated in terms of product fineness, powder flowability, color factor, surface adsorption characteristics, and agglomeration behavior. The study revealed that using any of the grinding aids tested improved the grinding process in comparison with the no aid condition. It was understood from the experiments and analyses that using OPO and OWW as grinding aids positively affected grinding performance. Particularly, the particle size analyses showed that the product fineness obtained in dry grinding tests was close to that obtained with commercial and pure grinding aids. Considering all the investigated grinding aids (except for OWW), powder flowability increased with the increasing concentration of the grinding aid. Remarkably, the OWW results demonstrated that the increase in dosage was not beneficial in terms of the ffp index. However, the enhancement of particle size was obvious. When evaluated in terms of product quality, four types of grinding aids increased total color differences with respect to feeding material and no aid test. Furthermore, the Fourier transform infrared spectroscopy (FTIR) conducted to determine the interaction between particle surfaces and grinding aids indicated that the grinding aids used in this study were adsorbed on the calcite surfaces by their non-polar, polar functional group and hydroxyl group. The analysis, in which the agglomeration phenomenon was examined with SEM (scanning electron microscopy) images, revealed that using grinding aids reduced the formation of agglomerates in comparison with the no grinding aid condition.

Erosion prediction due to micron-sized particles in the multiphase flow of T and Y pipes of oil and gas fields

The industrial pipeline components in the hydrocarbon and mineral processing plants may suffer erosion-induced damage and easily causes pipeline failure. This paper investigates a computational fluid dynamics (CFD)-Discrete particle (DP) modeling based on erosion prediction assessment of Tee (T) and Wye (Y) pipe configurations for gas-sand and water-sand flow conditions. The erosion under vertical-horizontal orientation was comprehensively investigated for 90° T-pipe, 45° Y-pipe, 30° Y-pipe, and 15° Y-pipe for different particle sizes. Finnie model is employed to evaluate the erosion rate and validated using qualitative and quantitative experimental results for the 90° T-pipe. Results manifest that the erosive wear is strongly influenced by the geometric configuration and erodent size. Particle trajectories show that particles in a 90° T-pipe tend to impact the junction of the pipe and rebound 2 to 3 times, which leads to a maximum erosion zone. The movement path of sand in the T-pipe is different from those of the Y-pipe, and one particle rebound is observed in the Y-pipe. Furthermore, the maximum erosive wear rate in the 15° Y-pipe is 3.36 times smaller than that of the 90° T-pipe.

Developing a data-driven soft sensor to predict silicate impurity in iron ore flotation concentrate

Soft sensors are mathematical models that estimate the value of a process variable that is difficult or expensive to measure directly. They can be based on first principle models, data-based models, or a combination of both. These models are increasingly used in mineral processing to estimate and optimize important performance parameters such as mill load, mineral grades, and particle size. This study investigates the development of a data-driven soft sensor to predict the silicate content in iron ore reverse flotation concentrate, a crucial indicator of plant performance. The proposed soft sensor model employs a dataset obtained from Kaggle, which includes measurements of iron and silicate content in the feed to the plant, reagent dosages, weight and pH of pulp, as well as the amount of air and froth levels in the flotation units. To reduce the dimensionality of the dataset, Principal Component Analysis, an unsupervised machine learning method, was applied. The soft sensor model was developed using three machine learning algorithms, namely, Ridge Regression, Multi-Layer Perceptron, and Random Forest. The Random Forest model, created with non-reduced data, demonstrated superior performance, with an R-squared value of 96.5% and a mean absolute error of 0.089. The results suggest that the proposed soft sensor model can accurately predict the silicate content in the iron ore flotation concentrate using machine learning algorithms. Moreover, the study highlights the importance of selecting appropriate algorithms for soft sensor developments in mineral processing plants.

Effect of oxidized pyrite activating persulfate on the degradation of aniline aerofloat: Mechanism and degradation pathway

Aniline aerofloat (dianilinodithiophosphoric acid, DDA) is a common flotation collector for sulfide minerals, but it is also toxic and difficult to be degraded. In this study, oxidized pyrite was used to degrade DDA through activating persulfate (PS). It was found that oxidized pyrite was far more effective than fresh pyrite at removing DDA from a PS system over a wide pH range. The effect of the pyrite oxidation time, initial pH, PS concentration, pyrite dosage and pyrite particle size on DDA degradation in the pyrite-PS system were studied and optimal conditions determined. Through analysis of the total Fe ions concentration, radical species identification and XPS analysis of the change of surface species Fe and S, the DDA degradation mechanism in the oxidized pyrite-PS system was determined. The degradation products were measured by gas chromatography-mass spectrometry (GC–MS) and a potential DDA degradation pathway was hypothesized. The results in this study suggest a template for the utilization of oxidized pyrite in gangue minerals to remove DDA from the wastewater in mineral processing plants.

Application of X-ray computed tomography scanning in describing partition curves of dense medium cyclones

The partition curve is an important tool to evaluate the separation performance of mineral separators like dense medium cyclones (DMCs). This curve is constructed by float-and-sink (FaS) analysis which involves the use of heavy liquids and suspensions. This traditional technique is hazardous to the environment, laborious, and time-consuming. Here, a new technique using X-ray computed tomography (XCT) scanning was successfully developed and applied for describing the partition curve of a DMC at an Australia-based lead–zinc mineral processing plant. The DMC feed, concentrate and reject streams were sampled and sieved into several size classes. The chemical assays and averaged densities according to each class were analysed by X-ray fluorescence spectrometry and gas pycnometry, respectively. The partition behaviour was investigated by XCT analysis. A model was proposed to determine the mass yield value – an important parameter to define partition curves – by mass balance and reconciliation, which is generally unknown during the sampling of continuous separation processes. From the reconstructed XCT images, we obtained detailed information on individual particles such as volume, surface area, mass, and density. Cumulative mass distribution curves and partition curves of the DMC for different size classes were then constructed and agreed with the FaS analysis. Using the XCT technology can help overcome the issues of the traditional FaS analysis. Moreover, this technology would allow for evaluating DMC separation efficiency with continuous, online, and real-time monitoring and control.

A 3D cellular automata ore stockpile model – Part 2: Simulation and industrial validation of dynamic discharging and trajectory segregation mechanisms

This paper describes a 3D cellular automaton (CA) for dynamically modelling ore piles with continuous feeding and discharging and incorporating two separate size segregation mechanisms. Stockpiles are an integral part of materials handling and storage, and their operation plays an important role in the overall performance of the mineral processing plant. Size segregation can create fluctuations and cause processing units to receive uneven feeds. However, this issue has not received enough attention. Therefore, a three-dimensional dynamic stockpile model has been developed at the Julius Kruttschnitt Mineral Research Centre (JKMRC), which can model the dynamic response of a wide-size-range stockpile. A Continuous Cellular Automata was developed, dividing the volume of the stockpile into a three-dimensional grid of cells with each cell containing an independent set of properties that are tracked throughout the simulation. Modelling size segregation during material flow was presented in Part 1. The variation in the stockpile surface profile and size distribution of the stockpile can be predicted. In this paper, the stockpile model with size segregation extends to the discharging and migration for real-time simulation. The model structure and industrial validation are discussed in this paper, which will show the application of the dynamic model, including the particle size distribution and the height variation of the stockpile. The three-dimensional dynamic stockpile model can contribute to the control of the comminution circuit because different operational strategies can be predicted using the model.

Research into the pressureless flow in hydrotechnical systems at mining enterprises

Purpose. The research purpose is to develop a mathematical model of a pressureless flow in a channel with the occurrence in some areas of overflow layer through the wall. Using this model, it is possible to calculate the overflow layer height and length, as well as the change in flow rate in the channel due to the withdrawal of part of the fluid as a result of the overflow. Methods. The research uses a comprehensive multi-stage analytical approach. Firstly, in order to develop a mathematical model for a pressureless flow in the channel with the occurrence in some areas of overflow layer through the wall, this research analytically determines the dependence of the flow rate through the channel wall based on formulas for calculating the weir discharge coefficient. At the second stage, a mathematical model of a hydraulic mixture pressureless flow in a rectangular channel with an overflow through the wall is developed to determine the parameters and flow regimes of the stream. Findings. The dependences of the dimensionless height of the overflow through the channel wall and the effective critical flow depth on the dimensionless current channel length have been obtained for various values of the acting force parameters and the process parameter of the fluid overflow through the channel wall. This made it possible to study the dynamics of changes in these values along the channel for various values of the specified parameters, and to assess the degree of influence of the relevant factors on the characteristics of the pressureless flow along the channel and the process of fluid overflow through wall. Originality. For the first time, the model of the pressureless flow in the channel is generalized for the case of occurrence in some areas of overflow layer through the wall, when the length and height of the overflow layer are not determined by a hole in the side surface, but are controlled by a decrease in the corresponding flow rate. For the first time, this model makes it possible to calculate the height and length of the overflow layer and the change in the flow rate in the channel due to the withdrawal of part of the fluid as a result of the overflow in cases of overflowing condition of the channel with the stream under unstable and non-calculated flow regimes. Practical implications. The mathematical model and the calculation results can be used to ensure the environmental safety of the logistics systems of mining enterprises, as well as to assess the volume of the environmental pollution in case of overflowing through the wall of the channels of pressureless hydraulic transportation of waste from mineral processing and metallurgical plants.

Effects of different heavy metal pollution levels on microbial community structure and risk assessment in Zn-Pb mining soils.

Heavy metal contamination in soils seriously threatens human health and aggravates the global pollution burden. In this study, we investigated the risk of heavy metal contamination in soils at a Zn-Pb mineral processing plant in Longnan, China, and the effects of different heavy metal contamination levels on diverse microbial communities. Statistical analysis showed that, except for Ni, the average content of all detected metals (Zn, Pb, As, Cu, Cd, Hg) in the soil was higher than the background value of soil in the study area, which was most seriously contaminated with Pb and As. Comparison of functional divisions showed that heavy metal soil contamination was most serious in the raw material stacking area and the production area. Interpolation analysis showed that areas closer to the wastewater discharge area had higher contents of each heavy metal and were more seriously polluted. From the point of pollution index, the risk of heavy metal soil pollution in the study area was very high (RI = 2845.24, i.e., > 600), with Cd and Hg being the most serious pollutants compared with other heavy metals. Microbial community abundance, diversity, and structure differed at different levels of heavy metal contamination. The community diversity of bacteria decreased with increasing heavy metal concentrations, while no significant change in fungi was observed. Evidence from variation redundancy analysis (RDA) and the Spearman correlation analysis showed that the leading factors affecting microbial community composition were Cu, Cd, Hg, and pH. Actinobacteria and Gemmatimonadetes at the uncontaminated level (CL) were significantly and negatively correlated with the concentrations of Cu, Zn, Cd, and Pb. Proteobacteria and Chloroflexi at the severely contaminated level (SL) were significantly correlated with pH and Hg. However, heavy metal contamination had less effect on most of the dominant fungi. In conclusion, microbial communities such as Proteobacteria, Actinobacteria, Chloroflexi, and Ascomycota showed greater tolerance to heavy metals. These results could be used as important references for the remediation of heavy metal-contaminated soils.

The State of Critical and Strategic Metals Recovery and the Role of Nuclear Techniques in the Separation Technologies Development: Review

The extraction of useful minerals or geological materials from the Earth’s crust, most typically from various sources, is crucial to a country’s development and progress. Mineral-rich countries use these resources to transform their economies and propel them toward long-term prosperity. There is an urgent need for the world to increase mineral exploration efforts, improve the recycling of important metal-containing resources, and extract them using upgraded hydrometallurgical procedures with high recovery efficiency. This review paper highlights the importance of strategic and critical metals in the economy and the role of nuclear techniques in the analysis, process optimization, and remediation of metals using solvent extraction, adsorption, and chromatographic resins. Radiotracer analysis, X-Ray Fluorescence spectrometry (XRF), Neutron Activation Analysis (NAA), and X-Ray Diffraction (XRD) are appropriate for improving laboratory-based hydrometallurgical processes, with future technical and economic benefits. The development and installation of novel instruments to provide the real-time control of mining and mineral processing plants for improved control have the potential to aid in the recovery of a broad range of metals.

Identification of abnormal conditions for gold flotation process based on multivariate information fusion and double‐channel convolutional neural network

AbstractAccurate and in‐time working condition identification plays a great role in industrial processes. However, most of the current flotation process identification models only use the characteristics of flotation froth as an identification basis, which often causes identification errors due to the instability of the froth, and a large amount of process data is not fully utilized. In this paper, an abnormal condition identification method based on multivariate information fusion and double‐channel convolutional neural network (double‐channel CNN) is proposed to achieve higher accuracy. First, a double‐channel CNN is used to extract depth features from different distributions of froth images and process data in parallel. Then, double normalized attention mechanism (double normalized AM) and multivariate information fusion methods are used to attach weights to the features and fuse them so as to ensure a higher response of key features and increase the reliability of the identification model. The method shows better performance than existing methods in offline simulations and has been validated online at a mineral processing plant in Shandong.

Development of a novel biocollector for flotation of low grade graphite ore

ABSTRACT Mineral processing plants operate in capacity of hundreds/thousands of tons per day. Accordingly, chemical reagents’ usage also increases proportionally. Stringent norms toward environment sustainability question the usage of chemical reagents, especially in large quantities and tailings disposal in open areas. Hence, bioreagents have gained great interest. Froth flotation is by far the most practiced processing route for fines beneficiation and low-grade ore upgradation especially for naturally hydrophobic minerals. Flotation being a physico-chemical separation technique, flotation reagents selection plays a pivotal role in the process performance. A novel environmental-friendly biocollector, an extract from the leaves of Vitex negundo, was used as flotation collector in the present investigation for beneficiating a low-grade graphite ore with 8.67% fixed carbon. A three-factor and three-level Box-Behnken Design (BBD) under Response Surface Methodology (RSM) was employed to study the effects of important process variables such as grinding time, depressant dosage, and collector dosage on the responses, namely, ash percent of final concentrate and its recovery. A final graphite concentrate with 4.24% ash and 14.42% yield was obtained using the developed biocollector by flotation of low-grade graphite ore with 89.47% ash content. The degree of significance of input variables was determined using ANOVA. Regression models for ash content, % of final concentrate, and its %recovery was obtained from BBD analysis. It showed that the grinding time has a significant influence on the process followed by depressant dosage on the grade of final concentrate and collector dosage on its recovery.

Comparing economic model predictive control to basic and advanced regulatory control on a simulated high-pressure grinding rolls, ball mill, and flotation circuit

Mineral processing plants remain nowadays infamous for their low energy efficiency. Economic model predictive control (EMPC), by directly considering the energy costs, could possibly help reduce their footprint, but its environmental benefits are yet to be clearly quantified. In an attempt to cast some light on this topic, this paper compares the response to a given ore feed size and hardness disturbance sequence of an EMPC to that of basic and advanced regulatory control systems using the profits and the specific energy (power draw/ore feed rate) as metrics. The simulated circuit comprises a high-pressure grinding rolls (HPGR), a ball mill, and a flotation circuit. It is based on population balance modeling and is an extension of previous works. The basic regulatory control (BRC) system comprises only single-input–single-output control loops with proportional–integral (PI) controllers and operates at a fixed feed rate. The advanced regulatory control (ARC) system consists of PI controllers maximizing the plant feed rate with override constraint handling. The results show that (1) ARC generates more revenue and maintains a lower circuit specific energy consumption than BRC, (2) ARC can produce the same economic performance as EMPC because the constraints of the system define the economic optimum, and (3) EMPC can trade revenues for a lower circuit specific energy with a hybrid criterion that penalizes power draw.

Optimization of magnetic separation of hematite contained in the depressed product from vazante mine s zinc ore flotation

The mining industry has seen a significant decline in mill feed grade in recent years, resulting in an ongoing build-up of materials not recovered at the mineral processing plants whose economic value has not yet been determined. Tailings dams have been the preferred method of disposal of such materials. However, recent dam breach events and the growing demand for mineral goods have enhanced the appeal of a more effective use of mined materials to prevent tailings accumulation and reduce social and environmental impacts, in line with the environmental, social and governance (ESG) principles that most companies have adopted. Different techniques can be used to recover economically valuable minerals contained in such materials, among which magnetic separation stands out for reasons of cost, production capacity, and recent developments of new equipment and matrices for wet high-intensity magnetic separators. The outcome includes gains in capacity, grade, and recovery yield. This paper assessed the use of a matrix developed by the company Gaustec, called BigFlux, in the magnetic separation of depressed product from the flotation process at Nexa Resources’s Vazante mine. Laboratory-scale magnetic separation tests were conducted using standard and an optimized matrix. For a 59% iron concentrate, the metallurgical recovery using such optimized matrix reached 72.6%, up 4% from the figure resulting from the use of the standard matrix, thus indicating that the use of the optimized matrix can improve the magnetite recovery process of the studied material.

A methodology to implement a closed-loop feedback-feedforward level control in a laboratory-scale flotation bank using peristaltic pumps

This paper describes the implementation of a level control strategy in a laboratory-scale flotation system. The laboratory-scale system consists of a bank of three flotation tanks connected in series, which mimics a flotation system found in mineral processing plants. Besides the classical feedback control strategy, we have also included a feedforward strategy to better account for process disturbances. Results revealed that the level control performance significantly improves when a feedforward strategy is considered.This methodology uses peristaltic pumps for level control, which has not been extensively documented even though: (1) peristaltic pumps are commonly used in laboratory-scale systems, and (2) the control implementation is not as straightforward as those control strategies that use valves. Therefore, we believe that this paper, which describes a proven methodology that has been validated in an experimental system, can be a useful reference for many researchers in the field.•Preparation of reagents to ensure that the froth stability of the froth layer is representative of an industrial flotation froth.•Calibration of instruments – convert the electrical signal from PLCs to engineering units.•Tuning PI parameters using SIMC rules by performing step-changes in each flotation cell.

A review on the Investigation of Hydrocyclone Performance by shape optimization

A hydrocyclone is a centrifugal classifier that separates particles by size using centrifugal force. Applications for hydrocyclones are incredibly varied. It is used to separate solids from liquids, liquids from liquids, and gases from liquids. It is easy to install and use, simple, inexpensive, and low maintenance. It serves as the brain of the mineral processing plant and is used to process water in important sectors of the textile, petroleum, chemical, paper, and agricultural industries. It is made up of a cylindrical and a conical portion. Three holes are present—two outputs and one for the feed intake. The under flow was for pollutant outlet and the vortex finder was for water outlet. Pressure drop, geometrical factors, and feed size distribution all have an impact on the hydrocyclone's efficiency. The present work reviews the shape optimization of vortex finder, spigots, air core and walls of the hydrocyclone for enhancing the desired outcome of the hydrocyclone.

Analysis of Benefits Between Sales Revenue and Transportation Cost of a Gold Mineral Processing Plant in Shandong

With the mining of gold mines, the gold level is gradually reduced, and the transportation cost of gold concentrate is gradually increased. This study analyzes the relationship between the analysis of different concentrate grades and transportation costs, so as to find the best economic benefits of the concentrator. A function is established in this paper. It is used to find the best economic benefit in different enrichment ratios. Raising the rate of recovery is not necessarily able to increase the total economic benefit of the concentrator. It was discovered by practice that the total economic benefit increased by 1109130 yuan when the recovery decreased by 0.22%.

ЭКСПЕРИМЕНТАЛЬНОЕ ИССЛЕДОВАНИЕ ХАРАКТЕРА И ПОСЛЕДСТВИЙ ВЗАИМОДЕЙСТВИЯ СОЛЯНЫХ ПОРОД С ГИДРОЗАКЛАДОЧНЫМИ РАССОЛАМИ ПРИ ПОДЗЕМНОЙ РАЗРАБОТКЕ МЕСТОРОЖДЕНИЙ КАЛИЙНЫХ СОЛЕЙ

Introduction. The research methodology included selection and comparative tests of strength characteristics of the initial core of sylvinite and carnallite in air-dry condition and, respectively, core samples after their contact with model hydrofilling brines. During the tests on the press under uniaxial compression load it was noted that most of the samples are very heterogeneous, characterized by layering and the presence of various inclusions, varying even within the same well. The specimens differ in the character of deformation at compression failure. It seems that the character of contact of targets with hydrofilling brines is different than in the soil of mine workings, through which drainage brines will flow, where the processes of frizzling have been revealed, indicating the influence on the development of fracturing of sylvinite protective pack in the soil and on the side walls of targets. The obvious risk of drainage brines penetrating into the cracks and the nature of their movement through the soil of the workings require full coverage of the sylvinite samples with brine from all sides. Research results. It is established that as a result of contact of samples of sylvinite rocks with saturated brine there is a decrease in strength characteristics by 1.2-1.7 times. It is determined that as a result of contact with model brines the deformation diagram of samples under load has changed. Monolithic sample of carnallite after incubation for 58 days in concentrated salt brine there was a complete loss of strength and the sample crumbled in a measuring cup. On the basis of the performed researches it is concluded that at hydrofilling of the excavated space with saturated hydrofilling brines there will be a decrease in strength of the contour part of the massif of chambers, pillars and in the soil of drainage excavations. Conclusion. In the laboratory experiment the fact of decrease in uniaxial compression strength of salt rock samples was established: already on the 36th day of ageing in brine the strength of samples decreased by 24-25%, deformation modulus - by 22-28%. On 56 days the compressive strength of the specimen decreased on average by 2 times in comparison with the initial ones in air-dry condition. It is also proved that at carrying out of hydrofilling works with application of saturated brines there is a decrease in strength of rocks of the contour part of the massif of chambers and drainage excavations. For the chamber being laid these processes are not so critical, but the influence of hydrofill brines on the strength and deformation modulus reduction for the underlying rocks at the base of drainage excavations, through which the excess brine will flow. Reduced strength and deformation characteristics may result in an increased risk of accidents at the underground mine. Resume. The influence of brines of the potash mineral processing plant on selected sylvinite cores has been assessed. Regularities of change of strength characteristics of sylvinite samples on uniaxial compression in «dry» state and after prolonged soaking in saturated brine of the processing plant were established.

Исследование горных пород горно-обогатительных комбинатов Мурманской области методом электроимпульсной дезинтеграции

Data on the general and specific energy characteristics of the electric pulse impact on rock samples of mining and processing plants of the Murmansk region, allowing to determine the required amount of energy in a pulse to achieve the effect of maximum release of useful components were obtained. The data of chemical analysis of rocks before and after electric pulse disintegration confirm the high efficiency of using the method to increase the release of useful components from rock samples of mining and processing plants were obtained. The results of the scientific work laid the foundation for research and development work by evaluating the effectiveness of the use of an electric pulse method on various rocks enriched at mining and processing plants for creation of an industrial electric pulse installation for mining processing plants.

Designing a copper mineral processing plant in virtual reality: A new tool for mining engineering education

In 2021, Queen’s University partnered with BBA Engineering Consultants to build a full-scale, virtual reality copper sulphide mineral processing plant. This project, financially support by e-Campus Ontario, aims to prepare Ontario post-secondary institutions to increase their training capacity in mineral processing to meet projected labour demands. The tool includes an environment where engineering students can work in real-time to diagnose problems in a high-fidelity and safe manner using virtual reality to sharpen real-life problem solving and design skills, so students are workplace-ready for employment in the mining industry. This paper examines the design process beginning with conceptual design, through detailed design and pilot testing. Various aspects of the project are discussed, including the agile project management approach, the importance of considering pedagogical objectives early in the project, the value of partnering with industry, and plans for further development of the tool.