How to cope with the challenges of sugar industry

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How to deal with the challenges of the sugar industry through digitalization

the full potential of digital sugar production lies in the seamless interoperability between people, assets, production processes and enterprise systems, as well as the effective use of available data


although each sugar producer faces its own specific manufacturing challenges, they also have some common challenges throughout the entire industry. Nowadays, the most urgent problem for enterprises is to optimize energy consumption, reduce material use and inventory costs, and improve asset utilization and output. Other issues that need to be prioritized include improving quality and reducing changes, errors and waste, while maximizing the traceability of materials and the implementation of relevant laws and regulations. These enterprises are ultimately eager to achieve an agile manufacturing environment. With the continuous development of IOT, industry 4.0 and digital technology, we can now find solutions for enterprises to meet these challenges directly. Here we will study how to apply technology to horizontal and vertical value chains. We believe that most digital systems today are not fully integrated. Companies, suppliers and customers are not closely linked. Engineering, production and service departments are no exception. The functions from the enterprise to the bottom of the factory are not fully integrated. Even the project itself (from products to factories to automation) lacks complete integration. However, with digitalization and industry 4.0, companies, departments, functions and capabilities will become more cohesive, and the cross company and general data integration network will continue to evolve, and realize the real automated value chain


the strategic goal of sugar producers is very simple: to provide competitive products, improve profitability and achieve business development in an environment of increasing globalization and rising product development costs

in achieving these goals, although each sugar producer faces its own specific manufacturing challenges, they also have some common challenges throughout the entire industry. Including:

optimize energy consumption

reduce material use and inventory costs

improve asset utilization and output

improve quality, reduce change, error and waste

maximize the traceability of materials and meet regulatory requirements

achieve an agile manufacturing environment

so how should we use digitalization to ensure that companies, departments, functions and capabilities become more cohesive? How to better integrate horizontal and vertical value chains? See figure-1 (Koch et al., 20141). How to ensure the evolution of cross company and general data integration network and realize the real automated value chain? Most importantly, how to solve the above six industry challenges through all these efforts

digitalization helps to establish a solid process data acquisition platform. This solves vertical integration by ensuring that process data is used for management decisions throughout the plant. Horizontal integration connects factories to the digital world, connecting suppliers and customers. (Koch et al., 2014)。

our starting point is to accurately understand what automation means and how different levels of process control affect the horizontal and vertical value chains found in the entire sugar production facilities

understanding automation

automation helps to perform continuous and repetitive operations, eliminating manual operations that would otherwise be required. Automation in the sugar production process can achieve high output, single form quality and high utilization rate of the factory, while reducing energy consumption and environmental impact

there are usually three types of automation:

- supervisory control and data acquisition (SCADA): covering network automation applications that have strict requirements for powerful remote communication, but do not require high-speed transmission and computing power

- programmable logic controller (PLC): for factory automation applications, it has high-speed requirements and many discrete i/o communication channels

- distributed control system (DCS): applied to process automation applications that require high computing power. There are two variants of DCS: core automation and extended automation. Core automation can be flexibly expanded and easy to use, mainly for small and medium-sized applications. Extended automation can provide users with more abundant information beyond the classic control range of DCS, and can integrate the power supply side of telecommunications, video and/or factories into the automation process

in addition, automation is also based on the following three types of field equipment:

measuring products: like the eyes and ears of factory operations

executive products: such as motors and drives, like muscles, can complete some work on site

control system: just like the brain and nervous system of a factory

in order to develop the automation interface between enterprises and control systems, we have introduced ansi/isa-95 standard and applied it to all industries and various processes, such as batch processing, continuous and repetitive. The purpose of ISA-95 standard is to provide consistent data, which is the basis for realizing the communication between suppliers and manufacturers

ISA-95 has five levels (level 0 to level 4), as shown in figure-2: (Scholten B, 20072)

figure-2: ISA-95 model

ISA-95 automation level

level 0 (field level) - defines the actual physical process and includes field equipment, such as flow and temperature sensors and final control components such as control valves

1 level (direct control) - defines the activities involved in perceiving and operating physical processes. It is the traditional instrument level of PLC system and controller and complete process controller. It includes input/output (i/o) modules and their related distributed electronic controllers

level 2 (plant monitoring) - defines activities to monitor and control physical processes. It includes sub process plant control for optimizing production, usually using advanced sensors or automatic analyzers directly in the process. PLC, SCADA and DCS operate here and collect all process data from level 1

level 3 (production control) - define the activities of the workflow and the final products required for production. It does not directly control the process, but monitors production and objectives. It includes the production coordination system of the whole factory to minimize costs and maximize output and quality control. Usually, these are managed by manufacturing execution system (MES), which analyzes and controls various elements in the production process in real time (such as personnel, input, equipment). This helps decision makers understand how to optimize the existing conditions of each plant to increase production. This is where manufacturing operations management (MOM) solutions come into play. Manufacturing operation management (MOM) is a comprehensive, scalable and modular suite, including process intelligence, manufacturing execution, production intelligence and production optimization. Using data from level 2, mom conducts historical trend analysis and key performance indicators analysis

Level 4 (production scheduling) - defines the business-related activities required to manage a manufacturing enterprise. It covers the enterprise resource planning (ERP) system and brings it to the next level by allowing companies to manage similar variables in multiple geographically dispersed production sites, while also automating many background functions. ERP transfers data to level 3 and then converts it into Level 2 actions

data transmission

figure-3 shows a practical example of how to apply the above ISA-95 model to the sugar industry. Exchange real-time data between level 0 and level 1. Process data is transmitted to level 2 monitoring and control (represented by material receiving, sending and shipping). At the same time, level 3 (represented by MES and mom) organizes and analyzes data and presents it in a form that makes it easier to make business decisions. Operational technology (OT) and information technology (it) data have been integrated here. Data sharing between Level 3 and level 4 (represented by ERP) is usually resources (personnel, equipment and materials), production capacity (available), product definition (how to make products), production plan (what to produce and use) and production performance (what to make and use). Level 4 shares this ot/it for horizontal integration

figure-3: data exchange between products and solutions in the sugar industry

mom is a modular system, so that customers can choose the modules to be executed. Mom contains many functions, but not all functions are required by users at the beginning. Figure-4 shows ABB's proposal to build mom in stages based on experience and customer feedback. In the first stage, it is recommended to use OEE and downtime management module. This means that the most basic data acquisition types are first implemented in the mom function module, and mom is expanded as the demand grows. For example, KPI dashboards, OEE and downtime management are relatively easy to implement and are usually easier to prove in terms of return on investment. At the same time, they also provide a solid foundation for adding other functional modules in the future

figure-4: it is suggested to gradually implement mom project

mom has a great impact on the sugar production process. TABLE-1 below gives a sample of some challenges, characteristics and benefits

TABLE-1: influence of mom on sugar production

sugar application library

in ISA-95 model, level 2 is DCS (arc consulting company, 20173), many of which are special software for the sugar industry. For example, ABB's sugar application library. It unlocks the data of every work function in the sugar industry: from managers who pay attention to profits to maintenance teams who continuously produce in key peak seasons

sugar making application is a complete, consistent and comprehensive software database for all sugar making process applications, from beet and sugarcane to refined sugar. It meets the requirements of all process areas, including raw material treatment, purification, evaporation, crystallization, saccharification and other processes. It also includes all utilities including biomass power plants, ethanol and water treatment

it is based on the knowledge gained through cooperation with major process equipment suppliers and sugar producers. This ensures that the latest process control concepts are incorporated into the application library. A typical example is the application library of vacuum batch tank with high-performance human-machine interface (HMI). As shown in figure -5. The figure on the left shows model recognition for better visual monitoring. This latest best practice allows the operator to visually monitor the control objects in the system. Pattern recognition is more effective than digital displays, deviation bars, and trends, allowing operators to more easily verify stable states while using large amounts of data

the figure on the right shows the high-performance HMI of the sugar making application library, which focuses on promoting the state perception of operators and their correct and effective response to abnormal situations

the application library contains various components for control and monitoring. Each component is a complete functional unit that can be used at any time and can adapt to specific user needs or process requirements

it is particularly important that the combination of DCS, mom and sugar application library can help users effectively solve the six challenges described at the beginning of this article. It achieves this goal by bringing together information technology (it) and operational technology (OT)

this digital combination provides users with the most advanced automation platform, which is the first time to optimize the process and electrical control of sugar plant equipment at the same time. Working with automation suppliers, sugar producers can design a well-defined automation strategy to ensure

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