DigitaIization in Manufacturing - IoT & Information Management

By Peter Leong, Head of Regional IT Apac, Petronas Lubricants International

Peter Leong, Head of Regional IT Apac, Petronas Lubricants International

The world of manufacturing has moved into a Fourth Industrial Revolution; Industry 4.0 is driving the Manufacturing Industry to bring with it a manufacturing environment which is more robust, resembles a smart manufacturing plant and has cybersecurity ready facilities to achieve more operational excellence. Industry 4.0 allows manufacturers to have more flexible manufacturing processes that can better react to customer demands.

Becoming a digital enterprise ensures that the productiveness of business partners are being utilized by their knowledge, which is spread across the enterprise. This will be central to manufacturing strategies which will be the major focus of all major initiatives as the success rate of this adoption will be directly measured by the impact on the bottom line. One strong advocate and leader of digitalization is none other than General Electric (GE) which has set-up GE Digital for the purpose of driving digitalization.

We will encounter more and more dramatic happenings of digital transformation in the manufacturing space as we move along from here and as the industry seeks to become more flexible and agile in its business practices, value chains, and customer offerings. The dramatic happenings are more so as digital transformation is projected to certainly drive the bottom line.

Manufacturers will look to adopt technologies in the coming years, which will allow them to transform their operating models with more digitally connect processes, procedures, and productions. This will then enable manufacturers to develop global standards that are much more flexible to accommodate regional businesses, customers, or product requirements.

There will be a time the Internet will enable unprecedented levels of network messaging between equipment, products and people, which means information on data collections about products usage, production capabilities, customer requirements and market requirements which will be analyzed for consumption and shared faster than ever before. This will be leveraging on big data and predictive analytics capabilities to be presented in business format will be analyzed for usage, will become much more prevalent. Big Data Analytics offers quick and easy access to operation, production, inventory, and other quality data, which enables managers and operators to adjust machines as needed across the enterprise. The Big Data Analytics will also involve some level of machine learning which also refers to cognitive computing, to obtain much faster and more accurate results.

There Will Be a Time the Internet Will Enable Unprecedented Levels of Network Messaging Between Equipment, Products and People

The advent of sensors in IoT, data collection—from areas stated in the manufacturing space, and presence of cloud technologies— for faster and more efficient data collection as well as the enormous amount of data storage—will surely assist in the cognitive predictive analytics and online/real-time generation of dashboarding reporting in bringing value to the business yields.

Cognitive computing will certainly assist manufacturers in identifying quality issues more efficiently, increasing production yield, and reducing problems that may lead to service and warranty costs particularly in the cases of manufacturing productions equipment. Downtime and reliability are critical when it comes to the operation of equipment on a shop floor. This will also help in minimizing and eliminating the potential of productions equipment from breaking down, by calling for immediate servicing or rectification prior to total breakdown.

Quality and yield are directly related to manufacturing processes, in the way raw materials are being utilized/used, processed, manufactured, and integrated into the end products quality.

Apart from this, IoT can also be implemented in manufacturing from the perspective of safety of production workers/employees by having sensors installed in the work equipment of production workers including safety helmet and any form of Personal Protective Equipment (PPE) – as the saying goes for a CEO would like to see the workers come to work safely and return home safely.

IoT is also pertinent as in the equipment parts of production line which can form the Inventory Management to ease the management of items or in the case of periodic audits of the inventory items. Thus, IoT will absolutely assist in the more efficient automation of such processes.

Only when data collected is being put into constructive usage, will it brings value to the business and management team for taking informed decisions. Thus, there are definite opportunities for further improvements and we look forward for much higher usage, in the mentioned areas, in near future.