Enterprises operating industrial control and automation systems, in a bid to increase profitability, are demanding ‘smarter’ shop floor operations, and are becoming ever more ‘data-driven’ in their decision making. IIoT and Industry 4.0 come with the promise of unlocking vast amounts of previously unavailable data from shop-floor devices and systems. In meeting this thirst for data, there is a significant engineering burden to correctly configure and connect devices and software systems.This paper presents two general approaches that allow connections between data sources and sinks in automation systems to be rapidly configured en masse. These techniques, scripting and model-based, can automate the manual, repetitive, and error-prone data point configuration task. A case study applying implementations of these techniques in a modern brewery’s process control and automation systems is presented. It demonstrates the significant level of reduction in configuration burden that has been achieved, especially in the case of the model-based approach.By utilitising these techniques, the cost, time, and error-rate involved in the configuration of industrial control and automation software systems can be greatly reduced. These improvements in engineering efficiency can lead to previously infeasible projects becoming achievable, and the extension of the lifetimes and capabilities of existing plants and equipment.

Contemporary environmental sustainability challenges coupled with rising energy costs compel the manufacturing industry to tightly monitor energy consumption. User-pays accountability systems are an appealing pathway to evoke genuine motivation to monitor and reduce energy consumption. This paper outlines the numerous issues and challenges associated with implementing such a system in existing manufacturing plants. A case study of a functioning user-pays system in a modern brewery is presented.

A novel architecture for a real-time Utilities Consumption Model (UCM) has been developed. The online UCM is capable of estimating the contributions from individual items of equipment towards the total instantaneous load of key utilities in a manufacturing plant. It also has the capability to forecast future consumption for areas of a plant that are scheduled. The UCM is a useful addition to the industrial control tool-set as it provides an effective means of minimising the energy impact of the timing and scheduling aspects of plant operations. A case study, demonstrating the application of the UCM at the Carlton & United Breweries (CUB) plant at Yatala, Australia, is included.

Process-related industries (many of which are inherently batch-related) account for a significant portion of the manufacturing sector. Many advances have been made in the field of process control, some of which are related to performance management of control loops. However, much of this work assumes continuous operation of the control loops. Many of the challenges presented by batch environments relate to a requirement to cater for both interruptions to control loops as well as varying plant dynamics. This paper provides both an overview of the general issues that are likely to be encountered in a batch environment as well as some deeper insights into a number of specific challenges. Some examples are provided based on experience within one of Australia's largest breweries. Despite this being a topic of emerging importance to manufacturing industries there is very little objective (non-commercial) information on these challenges available in the literature. This material will be of benefit to researchers who have an interest in realistic industrial control applications. It is also intended to be of use for those in industry by providing a realistic set of issues and challenges that are specific to batch environments.

A significant portion of industrial automatic control is powered by PID controllers. However there is little published literature on the details and quantity of controller types used in industry. Food and beverage represents an important segment of manufacturing in Australia. This paper presents a review of the automatic/regulatory control topology in one of Australia's largest breweries. Details of the site's 505 PID loops as well as the industrial networked control systems are included. As there is very little published material of this type it makes an important contribution to the existing literature. It is intended that this material can assist further research by providing evidence-based information on the quantity of controller types used in this segment of industry and details on some of the current issues and opportunities.

There is an increasing focus on sustainability in manufacturing industries. Operations management and plant/process control have a significant impact on production efficiency and hence environmental footprint. Information systems are an increasingly important tool for monitoring, managing and optimising production efficiency and resource consumption. An advanced Utilities Management System (UMS), that operates on the G2® real-time intelligent systems platform, has been developed at the Yatala brewery, Australia. An important characteristic of the UMS is its strong integration with the existing information and automation systems at the plant. The tight integration was required to maximise effectiveness and ease of use as well as to minimise development effort and cost.

A distributed fuzzy system is a real-time fuzzy system in which the input, output and computation may be located on different networked computing nodes. The ability for a distributed software application, such as a distributed fuzzy system, to adapt to changes in the computing network at runtime can provide real-time performance improvement and fault-tolerance. This paper introduces an Adaptable Mobile Component Framework (AMCF) that provides a distributed dataflow-based platform with a fine-grained level of runtime-reconfigurability. The execution location of small fragments (possibly as little as few machine-code instructions) of an AMCF application can be moved between different computing nodes at runtime. A case study is included that demonstrates the applicability of the AMCF to a distributed fuzzy system scenario involving multiple physical agents (such as autonomous robots). Using the AMCF, fuzzy systems can now be developed such that they can be distributed automatically across multiple computing nodes and are adaptable to runtime changes in the networked computing environment. This provides the opportunity to improve the performance of fuzzy systems deployed in scenarios where the computing environment is resource-constrained and volatile, such as multiple autonomous robots, smart environments and sensor networks.

Real-time intelligent system technology can be an effective means of optimising industrial operations. A large, intelligent Utilities Management System (UMS) has been developed at Foster's brewery in Yatala, Australia. The system is based on the G2 real-time intelligent system platform and it contains a number of modules that have been designed to improve the energy and utilities consumption of brewery operations. Of particular interest was the management and optimisation of the brewery's extensive Clean-In-Place (CIP) systems. The UMS monitors every step of every cycle of each CIP set and its real-time mass balance estimates chemical use and loss. An operator decision support system has also been developed that helps to minimise any redundant cleaning cycles. This system has been instrumental in lowering the bulk caustic soda consumption (per hectolitre of beer) of Yatala brewery by over 57% between the financial years F05 and F08.

Foster's brewery at Yatala have developed a G2-based real-time Utilities Consumption Model (UCM) of its plant. The UCM is used to estimate the instantaneous load of key utilities at the brewery. The contributions of individual equipment to the load profile can be estimated providing an unprecedented level of transparency into areas that are (in a metered sense) unmeasured. A case study is included that demonstrates the application of the UCM for load identification for the extensive refrigeration system that is critical for the brewery operations.

Manufacturing and mining automation, robotics, swarms and smart device networks are often implemented upon distributed embedded systems. These systems are typically statically distributed, coarsely recon﬿gurable or deployed on homogeneous networks. A conceptual stack can be formed using modelling languages, system performance analysis and optimisation and recon﬿gurable platform-neutral components to overcome these problems. A framework for computational intelligence-based applications to be built upon this stack has been proposed. Model-Driven Architecuture has been shown to be a promising standard for the modelling, design and development of embedded applications. The Theory of Constraints is proposed as a potential technique for performance analysis and optimisation of distributed systems. Mobile Agents and code mobility can be used in the component architecture to allow for adaptation and recon﬿guration for optimisation.

In recent times the ever-present drive to minimise the cost of production has been compounded with a strong focus on energy efficiency and environmental footprint. Previous activities such as updating old equipment with energy efficient replacements and plant maintenance & optimisation have all improved the cost of production to an extent. However an efficient plant doesn't guarantee efficient production. Intelligent systems can be used to monitor and improve the efficiency of the brewery. G2 is one of the world's leading real-time intelligent system development platforms. It is used by a significant number of the top Fortune 500 companies for a range of applications including control, scheduling, simulation, alarming and rule-based control. At the Foster's brewery in Yatala, Queensland we have implemented a large G2 system that has been configured to monitor both the plant and process control equipment. It monitors over 100,000 tags from 450 devices and it provides assistance in a number of areas including energy management and utilities & chemical consumption. A module for operator decision support has also been imple- mented for key areas of the brewery. In this module G2 presents a number of automatically prioritised recommendations to the operators in real-time. This system has helped us to both reduce production costs and to improve the reliability of the plant.