Process Flows, Mining Operations, & Chemical Engineering

Although there are opportunities to reduce electrical energy demand in unit processes of mechanical pulp-based paper and paperboard production, this may not be financially beneficial. This is generally because energy optimization opportunities connected to reduced refiner electricity demand in mechanical pulping systems also results in less steam available for the drying of the paper. As modern high consistency refiner systems produce approximately one ton of steam for each MWh of electricity when producing one ton of pulp, a reduction in electric energy demand leads to increased fuel demand in steam boilers to compensate for the steam shortage. In this study, the authors investigated what the financial and environmental situation would look like if they were to expand the system border from a paper mill to a larger system consisting of a mechanical pulp-based paper or paperboard mill, a district heating system with an incineration boiler and a chemical pulp mill. Mechanical pulp production has a wood to product yield of >90%, a high electric energy demand to separate woodchips to pulp and is a net producer of heat and steam while chemical pulp-based production has a wood to product yield of 50%, a low electric energy demand and is a net heat and electricity producer due to the combustion of dissolved wood polymers. The aim of this research is to create useful and robust models of how to use excess heat from certain industry sites to cover the steam shortage in other industry sites by means of utilizing and optimizing the district heating systems connecting these sites. For this purpose, the authors used the FrontWay module with ExtendSim which dynamically allows them to evaluate different scenarios. Their results shows that there is great potential to reduce both carbon dioxide emissions and production costs for industry sites and society by means of these tools.

Integrated sites are tightly interconnected networks of large-scale chemical processes. Given the large-scale network structure of these sites, disruptions in any of its nodes, or individual chemical processes, can propagate and disrupt the operation of the whole network. Random process failures that reduce or shut down production capacity are among the most common disruptions. The impact of such disruptive events can be mitigated by adding parallel units and/or intermediate storage. In this paper, the design of large-scale, integrated sites considering random process failures in addressed. In a previous work (Terrazas-Moreno et al., 2010), a novel mixed-integer linear programming (MILP) model was proposed to maximize the average production capacity of an integrated site while minimizing the required capital investment. The present work deals with the solution of large-scale problem instances for which a strategy is proposed that consists of two elements. On one hand, we use Benders decomposition to overcome the combinatorial complexity of the MILP model. On the other hand, we exploit discrete-rate simulation tools to obtain a relevant reduced sample of failure scenarios or states. We first illustrate this strategy in a small example. Next, we address an industrial case study where we use a detailed simulation model to assess the quality of the design obtained from the MILP model.

Simulations offer valuable insights into how an instrument can be expected to perform and can also point to areas for improvement. In the case of polarimeters described in this article, it is of interest to simulate the motion of the analysing polarizer relative to the fixed defining polarizer as this forms the basis for the optical rotation measurements. To make the simulation more realistic the author incorporated additional factors including (i) the broadband nature of the LED’s emission spectrum, (ii) the variation of the specific rotation of the sample as a function of wavelength, (iii) the spectral response of the detector and (iv) the temperature at which measurements are performed.

Mechanical sampling from conveyors has historically been a staple in the iron ore industry when information related to chemistry, sizing, and moisture is required. In order to optimize automatic sample stations in a changing production environment, BHP Billiton Iron Ore (BHPBIO) developed an ExtendSim model that enables the various combinations of mass–mass, mass– time, time–time and time–mass to be investigated. Their sample station model can utilize actual (variable) feed rates to achieve high resolution and enables the simulation of sample size variation. Cutter speeds and other settings can then be adjusted to better optimize the performance of the sample station with regards to optimal sample size. The model can also assist process engineers in adjusting settings to better optimize the sample station and reduce unwanted events such as blockages. The model can be easily modified to conform to various sample station designs. It is anticipated that the sample station model will be used by process engineers when looking at optimization and trouble shooting. The model is also being used as part of a training package to help new engineers understand the workings of a sample station and the impact minor adjustments to settings can have on sample mass and therefore compliance.

This paper addresses the design of large-scale, integrated sites considering random process failures. Using a novel mixed-integer linear programming (MILP) model, the authors are able to maximize the average production capacity of an integrated site while minimizing the required capital investment. In this case study, ExtendSim is used to analyze a scenario reduction technique, reporting the results of simulating the operation of the Pareto-optimal designs.

Value stream mapping (VSM) is a widely adopted method for transformation of production environments into a lean operational state. However, attributes of the ‘paper and pencil’ approach result in limitations when applying VSM in complex production environments. Using ExtendSim, an enhanced VSM method is developed featuring a feasibility and trade-off analysis which is incorporated into the VSM procedure. A case study covering a process of exhaust gas purification catalyst production is then conducted to test the newly developed method. The VSM project yields a shop floor lead time reduction from 11.4 to 1.4 d.