In an era where technology is reshaping industries at an unprecedented pace, manufacturing plants stand at the forefront of innovation. The integration of advanced IT infrastructure and systems has become the driving force behind optimising Operations, enhancing productivity, and propelling businesses towards a new era of efficiency. However, embarking on such a transformative journey requires strategic planning, meticulous execution, focused Change Management and a deep understanding of industry standards. In this guide, we delve into the intricacies of implementing IT infrastructure and systems in a new manufacturing plant, following industry best practice standards. From rigorous Programme and Project Management methodologies to robust cybersecurity measures, we leave no stone unturned. Get ready to unlock the full potential of your manufacturing plant as we explore the key pillars of success and chart a course towards revolutionising your Operations.
This article briefly discusses the following elements when approaching IT infrastructure and systems in a new manufacturing plant. Every topic requires extensive understanding and is too expansive to delve into fully. The aim is to provide high-level insight on topics that may need to be considered to ensure a successful IT implementation, as per the gunnercookeOP approach:
- Programme Management,
- Change Management,
- Project Management methodologies,
- Industry 4.0 and its Application in Smart Factories,
- AI and its Application in Smart Factories,
- Bridging the Gap for Smart Manufacturing,
- Vendor Selection,
- Manufacturing Operation Management Systems,
- Data Management and Analytics,
- Integration Across ISA-95 Levels and Existing Systems,
- Storage and Compute,
- Passive and Active Network Infrastructure,
- Civil work considerations,
- Local data centres,
- Front-End Applications or UI,
- Plant Commissioning.
This article forms part of a series of articles, written by gunnercooke Operating Partners (gunnercookeOP), which can be found here: https://gunnercookeop.com/news-and-insights/ . Some sections below may provide a direct link to specific topics which aims to provide more insight, however, these articles may still be under development and we encourage you to check back here again in the near future.
Budgeting accurately is crucial to ensuring the IT project’s success. A general rule of thumb would be to estimate a value of 5% of the overall new build project to be allocated against IT, covering only the topics covered in this article. This excludes other areas, such as Plant Control, Plant Equipment and sensors, PLM, ERP, etc.
Programme Management involves organising, planning, and controlling resources to achieve specific business objectives. Programme Management focuses on coordinating various activities, such as Project Management, Change Management and risk management to ensure that the overall programme is delivered on time, within budget and to the required quality.
It is vitally important to align critical IT elements with associated delivery phases of the overall programme, so interdependencies must be clear and individual project commitments must line up.
An example is to ensure that IT hardware, manufacturing systems and passive infrastructure are readily available; designed, developed, tested, deployed and commissioned in time for first product manufacture on the first production line.
Change Management involves managing the transition from the existing state to the desired state. Change Management focuses on identifying and addressing the impact of the changes on people, processes, and technology. It involves developing a comprehensive Change Management plan that outlines the scope, objectives, stakeholders, communication, training, and monitoring activities required to ensure that the changes are implemented smoothly and effectively.
For a new build, in some cases there may be no existing manufacturing capability, so the required IT Operational services will need to be built from scratch and integrated into existing hierarchies. In other cases, it may just be a case of expanding capability to take on the additional load. Either way, careful planning and execution of the transition of responsibility from the Programme teams to the Operational teams is required.
Project Management Methodologies
Project management methodologies involve the use of various tools and techniques to plan, execute, and monitor projects. Project Management methodologies focus on ensuring that the project is delivered on time, within budget and to the required quality. It involves using appropriate Project Management frameworks, such as Agile, Waterfall, or Hybrid, to manage the project activities, such as scope, time, cost, quality, risk, and stakeholder management.
The selection of methodology can be driven by the structure and organisation of the factory build programme or by the company culture – either way, the key goal is to ensure that key interdependencies that are dictated by the overall programme can be met effectively.
While Project Management and Programme Management share common elements, Programme Management operates at a higher level, focusing on strategic alignment, benefits realisation and managing the interdependencies among multiple projects. Project Management is more focused on executing individual projects within specific constraints.
Industry 4.0 and its Application in Smart Factories
Industry 4.0 refers to the fourth industrial revolution, characterised by the integration of digital technologies and automation into industrial processes. One of the key applications of Industry 4.0 is the concept of a smart factory, where advanced technologies are leveraged to optimise efficiency, productivity and flexibility. Smart factories employ a network of interconnected devices, sensors and machines that communicate with each other through the Internet of Things. This enables real-time data collection, monitoring, and control of various processes and equipment across the factory floor.
By collecting vast amounts of data from sensors, machines and other sources, smart factories can leverage big data analytics to gain valuable insights. Analysing this data helps in identifying patterns, optimising processes, predicting maintenance needs and making data-driven decisions to improve overall efficiency and productivity.
Smart factories utilise AI and machine learning algorithms to analyse data, detect anomalies and optimise production processes. These technologies enable predictive maintenance, intelligent quality control, demand forecasting and autonomous decision-making, leading to improved Operational efficiency and reduced downtime.
Automation plays a significant role in smart factories. Robots and automated systems are used to handle repetitive tasks, assembly processes, material handling and logistics. Collaborative robots (cobots) work alongside human workers, enhancing productivity and ensuring safety.
The manufacturing industry is undergoing a profound transformation fuelled by the concepts of Industry 4.0 and its successor, Industry 5.0. These paradigms bring together the power of digital technologies, automation, and data-driven intelligence to create a new era of smart factories. The application of Industry 4.0 and 5.0 principles is transforming manufacturing plants into highly efficient and agile production environments.
AI and its Application in Smart Factories
Artificial Intelligence (AI) is a transformative technology that has revolutionised numerous industries and the manufacturing sector is no exception. Artificial Intelligence (AI) has emerged as a game-changing technology with profound implications for the manufacturing industry, particularly in the context of smart factories. By harnessing the power of AI, manufacturers can unlock new levels of productivity, efficiency and decision-making capabilities.
One of the primary areas where AI shines in smart factories is predictive maintenance. By leveraging AI algorithms, manufacturers can analyse data from sensors and machines to predict equipment failures before they occur. This proactive approach enables timely maintenance, minimises unplanned downtime and extends the lifespan of machinery and equipment. By continuously monitoring equipment performance and detecting patterns or anomalies, AI-driven predictive maintenance helps optimise maintenance schedules, reduce costs and ensure uninterrupted production.
AI has emerged as a transformative force in smart factories, revolutionising maintenance practices, Quality Control, Production optimisation, decision support and human-machine collaboration. By integrating AI technologies into their IT infrastructure and systems, manufacturers can gain a competitive edge by improving productivity, product Quality and Operational efficiency.
Bridging the Gap for Smart Manufacturing
In today’s manufacturing landscape, the convergence of Operational Technology (OT) and Information Technology (IT) is revolutionising organisational operations. OT and IT convergence integrates traditionally separate domains, enabling smart manufacturing. OT encompasses technologies for monitoring and controlling physical processes, while IT focuses on information processing and data management.
Organisations are integrating OT and IT systems to enable seamless data exchange and real-time insights in manufacturing. This convergence bridges the gap between Operational and informational realms, driving efficiency and innovation. Challenges include technological differences, requiring careful planning and integration strategies, as well as data interoperability for meaningful exchange and analytics. Robust cybersecurity measures are necessary to protect critical systems and data.
OT and IT convergence empowers manufacturers by enabling real-time data acquisition, intelligent supply chain management and agile production planning. It enhances collaboration, knowledge sharing, and Operational Excellence by breaking down silos. However, organisations must address challenges, align cultures, develop a skilled workforce, implement scalable infrastructure and establish strong governance and security frameworks.
By overcoming these challenges, organisations can leverage the benefits of OT and IT convergence, achieving higher efficiency, productivity and innovation in manufacturing. Real-time data, advanced analytics and automation optimise processes and enable data-driven decision-making, allowing organisations to respond swiftly to market dynamics. Successful convergence drives smart manufacturing and unlocks the full potential of digital transformation.
Choosing the right vendors and suppliers is crucial for managing costs effectively. It is important to evaluate multiple vendors based on their capabilities, reputation, cost competitiveness and ability to meet the project’s requirements. Requesting detailed proposals and comparing them against the project’s budget can help in selecting the most cost-effective options.
Manufacturing Operation Management Systems
Manufacturing Operation Management systems involve the software components that support the management and optimisation of the manufacturing processes and Operations in the manufacturing plant. Manufacturing Operations Management (MOM) is a set of practices, systems, and tools used in manufacturing to plan, execute and manage the entire production process. The goal of MOM is to optimise production efficiency, reduce costs and increase Quality and profitability.
MOM involves a wide range of activities, including resource planning, production scheduling, inventory management, quality control, and performance analysis. It provides real-time information about production processes, equipment status, and inventory levels, allowing manufacturers to make informed decisions and adjust production plans accordingly.
As explained in the ISA-95 standard, Manufacturing Operations Management is the collection of Production Operations Management, Maintenance Operations Management, Quality Operations Management, Inventory Operations Management and other activities of a manufacturing facility. These categories of Operations are composed of a collection of activities and each activity is composed of a set of tasks.
Data Management and Analytics
Data management and analytics involve the process of collecting, storing, processing and analysing the data generated by the IT infrastructure and systems in the manufacturing plant. Data management and analytics focus is on designing and implementing the data architecture that meets the requirements for data quality, data governance and data analytics. It involves selecting the suitable data management technologies, such as databases, data warehouses or data lakes and the appropriate data analytics technologies, such as predictive analytics, to ensure that the data generated by the IT infrastructure and systems in the manufacturing plant are effectively managed and analysed to support the decision-making processes in the manufacturing plant.
Integration Across ISA-95 Levels and Existing Systems
Integration across ISA-95 levels and existing systems involves the process of connecting and exchanging data between the IT infrastructure and systems in the manufacturing plant and the existing systems and equipment in the manufacturing environment.
The term ‘manufacturing plant’ refers to the physical location where the manufacturing processes take place, including the building, machinery, and equipment used for production. The term ‘manufacturing environment’, on the other hand, refers to the broader context in which the manufacturing plant operates, including external factors such as supply chain logistics, regulatory compliance and market demand.
When integrating IT infrastructure and systems in a new manufacturing plant, it’s important to consider how these systems will interface with the existing systems (such as ERP and PLM) and equipment in the manufacturing environment as a whole, not just within the plant itself. This may include integrating with suppliers and customers, coordinating with regulatory agencies and optimising supply chain logistics to ensure that the manufacturing plant operates effectively and efficiently within the broader manufacturing environment.
Integration across ISA-95 levels and existing systems focus is on designing and implementing the integration architecture that meets the requirements for interoperability, scalability and security. It involves selecting the suitable integration technologies, such as OPC UA, MQTT or RESTful APIs and the appropriate integration patterns, such as point-to-point, publish-subscribe, or hub-and-spoke, to ensure that the IT infrastructure and systems are seamlessly integrated with the existing systems and equipment in the manufacturing environment.
The amount of data integration can vary significantly depending upon the levels of automation and decision making required. Point-to-point connectivity of multiple systems may be possible but can become very complex, very quickly. Messaging layers are often selected as the most effective way forward as all systems can be connected into the messaging layer and the data shared amongst all other connected systems.
Storage and Compute
Storage and compute involve the hardware and software components that support the processing and storage of data in the manufacturing plant. Storage and compute focus is on designing and installing the appropriate storage and compute infrastructure that meets the requirements for scalability, performance and availability. It involves selecting the suitable storage technologies, such as SAN, NAS, or cloud storage, and the appropriate compute technologies, such as virtualisation, containers, or bare metal servers, to support the processing and storage of data in the manufacturing plant.
Passive Network Infrastructure
Passive Network Infrastructure involves the physical components, such as cables, connectors and racks that support the transmission of data across the network. Passive Network Infrastructure focuses on designing and installing the network components that meet the requirements for reliability, scalability and performance. It involves selecting the appropriate network topology, the suitable cabling and connector standards, such as Cat6, fibre optic, or copper, to support the data transmission across the network.
Consider having spare data cabling installed to accommodate future growth and unexpected requirements, as having to add it afterwards can be costly.
Active Network Infrastructure
Active network infrastructure involves the electronic components, such as switches, routers and firewalls that manage the transmission of data across the network. Active network infrastructure focuses on designing and installing the network components that meet the requirements for security, availability and performance. It involves selecting the appropriate network protocols, such as TCP/IP, SNMP, or HTTP, and the suitable network devices, such as switches, routers, or firewalls, to support the data transmission across the network.
Redundancy involves the process of designing and implementing backup and failover mechanisms that ensure the availability and continuity of the IT infrastructure and systems in the manufacturing plant. Redundancy focuses on designing and implementing the redundancy architecture that meets the requirements for high availability, fault tolerance and disaster recovery. It involves selecting the suitable redundancy technologies, such as clustering, load balancing or replication and the appropriate redundancy strategies, such as active-active, active-passive, or hot-cold, to ensure that the IT infrastructure and systems are always available and resilient in the face of disruptions or failures.
Cybersecurity involves the process of designing and implementing security mechanisms that protect the IT infrastructure and systems in the manufacturing plant from cyber threats, such as malware, hacking or phishing attacks. Cybersecurity focuses on designing and implementing the cybersecurity architecture that meets the requirements for confidentiality, integrity and availability of data and systems. It involves selecting the suitable cybersecurity technologies, such as firewalls, intrusion detection and prevention systems, or encryption, and the appropriate cybersecurity policies, such as access control, risk management, or incident response, to ensure that the IT infrastructure and systems are secure and compliant with the relevant regulations and standards.
Civil Work Considerations
Civil work considerations involve the physical components, such as buildings, facilities and infrastructure that support the operation of the manufacturing plant. Civil work considerations focus on designing and constructing the physical infrastructure that supports the operation of the IT infrastructure and systems in the manufacturing plant. It involves selecting the suitable construction technologies, such as pre-fabrication, modular construction or green building and the appropriate construction standards, such as LEED, BREEAM, or WELL, to ensure that the physical infrastructure supports the operation of the IT infrastructure and systems in a sustainable, efficient and safe manner.
Considerations for primary and secondary pathways should be planned and constructed for data cabling where necessary. Careful planning can reduce costs significantly, as having to introduce new paths by uplifting newly established groundworks can be costly.
Local Data Centres
Local data centres involve the physical components, such as power, cooling and security that support the operation of the IT infrastructure and systems in the manufacturing plant. Focus is on designing and installing the data centre infrastructure that meets the requirements for reliability, security, and scalability. It involves selecting the suitable data centre design, such as tiered, modular, or containerised and the appropriate data centre components, including redundancy, such as UPS, generators, cooling systems, fire suppression and security systems, to support the operation of the IT infrastructure and systems in the manufacturing plant.
Front-End Applications or UI
At the manufacturing level, it may be possible to rely upon the Human Machine Interface (HMI) equipment that controls individual machines, but from a management perspective it will require the capability to combine data from numerous sources to aid with decision making at multiple layers such as manufacturing processes, quality control, building management and strategic planning.
Plant commissioning involves the process of testing and verifying the operation of the new manufacturing plant before the start of production. Plant commissioning focuses on ensuring that the IT infrastructure and systems are tested and validated to ensure that they meet the requirements for reliability, availability and performance. It involves developing a comprehensive commissioning plan that outlines the test procedures, acceptance criteria and documentation required to ensure that the IT infrastructure and systems are fully operational.
For new factory builds it can often be a simple case of testing and commissioning the IT environment at the same time as the rest of the manufacturing facility, but there will often be variations that require special management. Having the capability to test changes to a manufacturing environment, without utilising all the production manufacturing equipment will be a must – developing the right level of testing capability will need to be based on an appropriate assessment of risk. The result could range from a light touch test rig, which checks basic data flows, right through to a complex virtual factory that allows end-to-end replication of the systems and their impact on the manufacturing equipment.
Industry 4.0 and Industry 5.0 revolutionises traditional manufacturing processes by incorporating digital technologies, connectivity, and automation. Smart factories leverage IoT, big data analytics, AI, robotics, digital twins, and cybersecurity to achieve higher levels of efficiency, productivity, flexibility, and innovation in the manufacturing industry.
Implementing IT infrastructure and systems in a new manufacturing plant requires a comprehensive and systematic approach that considers the various aspects and components of the IT infrastructure and systems, as well as the manufacturing environment and processes. By following international standards and best practice principles, the implementation process can ensure that the IT infrastructure and systems are designed and implemented in a way that aligns with the business objectives, meets the Operational requirements and complies with the relevant regulations and standards. This article briefly explains some of the topics to provide a flavour for what one may need to consider when building a new facility.
gunnercookeOP are continuously monitoring developments and reporting on all of the identified topics with new articles regularly posted to: https://gunnercookeop.com/news-and-insights/
Our mission is simple: to help Investors, Owners, and Leaders grow and improve their businesses. We offer pragmatic solutions that fit your specific requirements, building a toolkit of practices that support performance improvement and the adoption of change.
We look forward to having a conversation with you!
Should you require further assistance and wish to have a conversation to explore more, contact the author as follows:
John Hannah – gunnercookeOP
Erol Cacouratos – gunnercookeOP