Industry 4.0 : Production Scheduling

What is Industry 4.0?

Industry 4.0 is an evolving concept but broadly refers to the increased automation and data exchange in manufacturing operations, benefiting from new technologies such as Internet of Things, Artificial Intelligence, robotics and cloud computing.

This technology is expected to significantly increase productivity, and could have significant implications for the economics of manufacturing operations and distribution of industrial operations, both at the national and global level.

Production Software and Industry 4.0

Industry 4.0 is a significant opportunity for MJC² as it provides a new source of real-time data that can be used by our production scheduling algorithms to increase efficiency in manufacturing operations.

At the same time it presents new and exciting challenges in terms of changing the way manufacturing operations are managed and scheduled, particularly in the context of robotics, data sharing and additive manufacturing.

Artificial Intelligence & Autonomy

Artificial Intelligence is both an enabler and a driver for MJC²'s production software. AI allows us to build faster and more powerful optimization algorithms, which tackle problems that are outside the scope of other technologies.

This translates into a direct cost benefit through increased efficiency, typically around 10% depending on the nature of the operation. Furthermore it means that manufacturers can offer more flexible service to their customers, while reducing their environmental footprint.

At the same time, increased use of AI in related areas such as robotics, quality control, safety and understanding consumer behaviour presents new opportunities for applying real-time scheduling algorithms.

For example a fully automated production line can be scheduled in a different way to one that involves human intervention, while the data coming from e-commerce platforms can be used to respond better to demand.

Data Sharing & Collaborative Planning

Distributed manufacturing operations already share significant volumes of data, but the availability of cloud-based technologies and increasingly complex supply chains mean that inter-company data integration will increase, provide parallel cybersecurity developments ensure secure and reliable communication.

MJC²'s PIMSS and DISC software exploit this increased availability by facilitating collaborative planning, not just between the manufacturing sites/facilities in the supply chain, but also between manufacturers and logistics partners.

This integration increases reliability and synchronisation along the supply chain, while also increasing resilience, and of course creating opportunities to reduce cost through better use of transport resources.

Internet of Things

IoT increases the availability of real-time data, captured from field/plant devices and controllers, smart pallets and containers, and even from smart products as they are manufactured. Similarly, the real-time connectivity allows faster and more detailed fine-tuning of the production plan in response to actual events.

Without appropriate big data analytics and optimization tools in place however there is a danger than the human planner or manager simply becomes swamped with information, and ultimately ends up ignoring or misinterpreting it.

MJC²'s production software already takes a significant step towards solving this issue, using algorithms developed for managing real-time data received from logistics and transport operations. Artificial Intelligence algorithms can detect anomalies and automatically respond to many situations, only requiring human intervention for genuinely exceptional or serious situations.

Additive Manufacturing

Additive manufacturing and related 3D printing technology is likely to significantly change the manufacturing landscape. Centralised stocking of spare parts and products may be replaced by a network of local, more flexible production facilities which can respond quickly to customer demand.

From the production planning and logistics scheduling perspective this presents an interesting real-time optimization problem that we believe MJC²'s algorithms are well-suited to tackle.

Line scheduling and sequencing of production runs on 3D printers will need to be optimized to minimise changeovers and downtime, while intelligently prioritising orders based on urgency and ongoing logistics considerations.

Increasing complex last-mile delivery constraints and operations are likely to mean more use of different delivery modes: electric vehicles and e cargo bikes already exist, and there is a lot of attention on new technologies such as drones and hyperloop.

 

 

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