Scaling IIOT for Manufacturing
(6 minute read)
Amidst the plethora of digital technologies that are expected to impact in manufacturing, the one with the clearest push for investment is the Industrial Internet of Things (IIoT), also known as Industry 4.0. Drawing from analysis by McKinsey, this blog highlights some approaches to better integration of IIoT in manufacturing.
Digital connectivity has allowed manufacturing companies to enhance organisational resilience during the pandemic. Manufacturers have been able react to changes in market conditions quicker and more efficiently by adapting production processes even remotely through digital tools. Yet despite lowering costs of IT investments and improvement in IIoT integration, IIoT uptake and upscale has been slower than expected, even when there are proven operational and financial benefits to be gained.
Challenges
Many technical and organisational challenges hinder greater uptake of IIoT. Organisations still deal with the technical challenges of coping with legacy heterogeneous systems, application landscapes, decisions around which operational functions should be supported by applications and also where they should be deployed within their manufacturing chain. Organisational challenges like outdated business processes, lack of vision and appropriate leadership means that value potentially derived from IIoT is left on the table.
A useful report from McKinsey, Leveraging Industrial IoT and advanced technologies for digital transformation in manufacturing, outlines seven enablers within three major domains of work as roadmaps:
- Business
- Identifying a use case and prioritising
- Rollout and enablement
- Organisation
- Change and performance management
- Capability building and new ways of working
- Technology
- IIoT and data infrastructure
- IIoT and platform
- Ecosystem
IIoT and Business
Manufacturers should identify, prioritise, and roll out use cases. Using both top down and bottom up approaches, companies should identify and prioritise use cases based on their financial impact and ease of implementation. Use cases can be considered for their potential for replication and rollout across the entire manufacturing network. They need to consider challenges in scaling up including training, implementation, and support to ensure there is an overarching case for adaptation.
IIoT and Organisation
Organisational barriers typically range over performance management, building capabilities, and shaping overall culture. Performance management covers the technological aspects of IIoT including setting clear targets, allocating responsibilities, monitoring implementation, control, and mitigation. Priming the organisation for IIoT success means effecting changes to organisational structures, collaborations, job roles, training, and shaping new ways of working. This also involves setting up common governance models, harmonised processes and central data security and management.
IIoT and Technology
Tech related decisions will cover three levels: platform, cloud, ecosystem. Platform design focuses on target architecture of IIoT, and decisions around integrating IT and OT, which can sometimes be incompatible. To achieve integrated technology stack, manufacturers need to carry out status assessment, plan for future targets to select use cases, and decide on partnerships, training, and cybersecurity. Cloud imperative decisions will need to consider overall value to the business as cloud provides access to AI and ML engines, links to new products, opportunities, and partnerships within the ecosystem, and a sandbox environment for experimentation. Companies need to consider migration plans and sequence for cloud switch. Ecosystems will also be essential depending on whether manufacturers want to build one or simply join an existing one. Companies should focus on basics such as creating and securing a solid platform and data in order to extract value from an IIoT ecosystem. The ecosystem should also have sufficient variety and diversity of skills and partnerships as a highly diverse ecosystem can offer numerous opportunities at scale.
The above considerations can help manufacture extract maximum value from IIoT.
