Most people working in an industrial or technology field will have heard of the so-called 4th Industrial Revolution (4IR) and this is a hot topic in South Africa’s various government departments. It refers to the ready availability of massive computing power to enhance the effectiveness of industrial manufacturing and supply chain systems. Wikipedia refers to Industry 4.0 as “… the current trend of automation and data exchange in manufacturing technologies, including cyber-physical systems, the Internet of things, cloud computing and cognitive computing, and creating the smart factory”. The essence of 4IR thinking is to couple computing power to manufacturing processes and supply chain logistics to enhance decision-making and automation, thereby improving manufacturing productivity and reducing production and distribution costs.
Staged approach to Industry 4.0
Sugar Factory 4.0
South African sugar factories, and indeed sugar factories throughout most of the world, are facing severe challenges, and the need to reduce costs of production and improve process efficiency is paramount. However, such factories are characterised by variable raw material feedstock, changing process conditions, a high degree of complexity, and multiple recycle loops. There are many instruments, measurements and control systems in a sugar factory, with lots of analytical and process data available, with even more becoming available as the SMRI’s Near Infrared Spectroscopy (SMRI-NIRS) analytical technology is being deployed. However, these data are not always readily accessible to the operating staff and may not be easily interpreted in order to improve efficiencies and troubleshoot problems. The Sugar Milling Research Institute NPC (SMRI) considers that there is great potential for the application of 4IR principles to sugar factories to improve declining performance and, following a successful application, was able to attract funding from the national Department of Science and Innovation (DSI) Sector Innovation Fund and the sugarcane processing industry to undertake a project to develop and implement relevant 4IR solutions in the industry.
Factory focus areas
Kitty Foxon
Through a workshop with sugar factory and company representatives, several sugar factory process sections were identified that could potentially benefit from the application of process data-based 4IR principles to improve efficiency or profitability. One shortcoming of the current system of factory sampling, analysis and calculation procedures is that relevant process parameters may only be available hours or days after sampling, thus providing a historical perspective on operations. What would be more valuable is near real-time data and derived information that can inform operators of the current performance status to permit them to make changes to improve performance. 4IR tools could further provide predictions of future performance trajectories in order to make pro-active decisions to minimise losses.
It was recognised that the hardware and software skills required to implement 4IR projects in the sugar industry were not widely available, but there are numerous companies and consultants with such skills available. However, to maximise the benefits of such projects, domain-specific knowledge is required, i.e. sugar technology and factory operational knowledge and skills. Thus, calls were put out for proposals involving 4IR consultants, SMRI teams and factories that had an interest in testing 4IR solutions. This process, under the SMRI team leadership, namely Ivan Voigt, Steve Davis and Dr Kitty Foxon, resulted in the approval of six technical and value assessment (TVA) projects, which aim to identify how the 4IR principles could be applied to each particular problem area, the costs of such implementation and the savings/increased productivity that could be realised from the implementation.
Following project set-up meetings and contracting, the host factories were visited to understand the nature of the problems and what data may be available and would be needed to develop appropriate solutions. Certain projects were extensions of existing SMRI research projects, which meant that considerable data collection and interpretation had already been done, enabling the process to be fast-tracked. The following six TVA projects have been undertaken, with the recommendations of the consultants having now been received.
- C-Centrifuge monitoring (at two factories with two consultants). The C-centrifuge station is the last opportunity to recover crystal sugar; sucrose passing through to molasses is lost. Operational factors that are associated with or lead to high sucrose loss to molasses will be studied in and monitored in this project and deviations from best practice will be highlighted in order for the operators to focus on bringing process parameters back to optimum values.
- Inversion losses / non-sucrose tracking. Undetermined sucrose losses in a factory are typically only assessed at the end of each week, by which time it is too late to correct problems. However, there may be multiple reasons for such losses and assessing root causes in real time is a complex task. This project seeks to utilise the rapid analytical capabilities of the SMRI-NIRS technology to track sucrose inversion and non-sucrose creation in the raw house for early identification of loss-causing situations, as well as monitoring process conditions that are typically associated with high sucrose losses.
- Throughput control. In a sugar factory, there may be several process bottlenecks that limit production capacity, and these change throughout the season. The Throughput project will analyse process data to identify where process bottlenecks are occurring that may lead to a negative impact on production and recovery. The products are anticipated to be software tools for bottleneck forecasting and scheduling to minimise the occurrence of such bottlenecks by pro-actively making appropriate process decisions.
- Diffuser operations. Sugarcane diffusers are effective devices to extract sucrose from cane but controlling them to optimise performance at lowest energy cost is a complex task. This project will take existing and new diffuser process data to develop better insights into diffuser operation and control to improve sucrose extraction without excessive use of imbibition water.
- Steam supply and usage. A sugar factory has a highly integrated steam supply and demand network to maximise the use of energy extracted from bagasse, sometimes supplemented with coal. However, there are few places where energy usage is effectively measured. This project aims to monitor and interpret high- and low-pressure steam supply and demand patterns so as to improve factory energy efficiency, especially where the cost of coal usage is considerable.
Steve Davis
The six TVA reports will consider how these projects may be implemented at these factories, the costs associated with the hardware and software for such, and the technical and financial benefits that may be expected to accrue to the factories following successful implementation. In December 2019, the project Steering Committee will approve the recommended projects to be implemented in 2020. Consideration will also be given as to how such projects may be rolled out to other factories if successful, and it is anticipated that the industry will see a step-change improvement in performance in a few years through the introduction of such 4IR thinking and technology.
