FAQs
The Industrial Revolution, otherwise known as Industry 1.0, started in the late 1700’s, which introduced mechanical production with the assistance of water and steam. Industry 4.0 is the latest transformation within automation and industry, built around the ethos of using cyber-physical systems, which can monitor and augment existing processes, in just about all manufacturing processes, across all segments.
In the last decade, massive technology pillars have been in development like cloud computing, big data, and mobile computing. It’s these types of pillars that have enabled the Industry 4.0 movement and, in turn, will allow the vision of the smart factory to become reality. Industry 4.0 is the next industrial revolution that represents the connectivity between industrial equipment and constant data flow to access and analyze centralized information.
As industry is beginning to leverage these capabilities, we’re now able to capitalize on these trends to make advanced technologies possible; we’re at a really exciting turning point where we can drastically change and improve the way we work and shatter the conventional ways of doing things.
These cyber-physical systems are typically connected using an “Internet of Things” mentality, allowing a fast and accurate flow of information back and forth, enabling the end user to make real time, decentralized decisions about the production capabilities of his or her manufacturing facility, thereby creating a connected and digitized “smart plant”.
The Internet of Things (IoT) is the connection of people, processes, data and things over an IT network. For businesses, the IoT is at the centre of the merger of Information Technology (IT) and Operational Technology (OT) as data is collected to gain insights, optimize processes and create opportunities. Enabling this connectivity of machines and equipment on the factory floor is one element of Industry 4.0, so the IoT is a component of Industry 4.0.
Industry 4.0 solutions improve the efficiency, quality, and utilization of factory operations. The Business Development Bank of Canada released a report in June 2017 that showed 60% of Canadian manufacturers who adopted Industry 4.0 solutions experienced a boost in factory productivity. Nearly 50% reduced operating costs, and 42% improved product quality. Simply put, Industry 4.0 helps manufacturers make more, in less time, for fewer resources.
The manufacturing industry has always focused on building out lean processes. Consumers want things faster, cheaper, and expect better quality than ever before. So, it keeps operators on their toes leaving them to ask: how do I build a product with the highest throughput, lowest cost, least amount of material and fastest cycle time? And once manufacturers crack the code on creating a lean process, they challenge themselves to push further through continuous improvement.
Through this workshop we engage with participants at all levels primarily to ensure that all involved have common understanding of the subject, the challenges, the risks, the benefits, the change management aspects etc. The workshop is conducted at least at two levels, if not more.
The following areas and KPA related to each will be the basis of the study and workshop.
• Product Governance
• Process Support
• Digital Collaborative Environment
• Digital Data Strategy
• Production Management
• Virtual Development
• Requirements Management
• System Design
• Supply Chain Integration
• Change Management
• Resource Management
• Physical Development
• Service Management
The following areas and KPA related to each will be the basis of the study and workshop.
• Product Governance
• Process Support
• Digital Collaborative Environment
• Digital Data Strategy
• Production Management
• Virtual Development
• Requirements Management
• System Design
• Supply Chain Integration
• Change Management
• Resource Management
• Physical Development
• Service Management
“Big data” is an all-inclusive term used to describe vast amounts of information. In contrast to traditional structured data which is typically stored in a relational database, big data varies in terms of volume, velocity, and variety. Big data is characteristically generated in large volumes – on the order of terabytes or exabytes of data (starts with 1 and has 18 zeros after it, or 1 million terabytes) per individual data set. Big data is also generated with high velocity – it is collected at frequent intervals – which makes it difficult to analyze (though analyzing it rapidly makes it more valuable).
It involves gathering hundreds of thousands of terabytes of information, compiling all of that information into sections, and analyzing it for patterns, inconsistencies, or faults.
However, a well-known explanation to help you understand big data is the 3Vs:
• Volume: The amount of data in which you are trying to access. This includes transaction-based data or online shopping, sensor and machine-to-machine data, data from social media accounts, and much more.
• Variety: The different types of data that can be used to compile information. Types of data such as spreadsheets, databases, text files, images, video, music, and more are the variety sources.
• Velocity: The speed in which the data is captured. Consider the fact that there are 300 million photos posted to Facebook each day, 5 new profiles created each minute, and over 293,000 status updates are posted every sixty seconds. Being able to weed through all of the data and only select the important pieces -- quickly -- is velocity.
Big data can come from a variety of sources, ranging from customer data, social media data, or the Internet of Things (such as GPS navigation, cars, home automation, and more). It is capable of producing information about just about every aspect of your customer's life in the form of a data trail, and if analyzed correctly, can lead to a better understanding of their lifestyle and purchasing habits. Or in simple words we can say “Big Data includes data sets whose size is beyond the ability of traditional software tools to capture, manage, and process the data in a reasonable time.”
It involves gathering hundreds of thousands of terabytes of information, compiling all of that information into sections, and analyzing it for patterns, inconsistencies, or faults.
However, a well-known explanation to help you understand big data is the 3Vs:
• Volume: The amount of data in which you are trying to access. This includes transaction-based data or online shopping, sensor and machine-to-machine data, data from social media accounts, and much more.
• Variety: The different types of data that can be used to compile information. Types of data such as spreadsheets, databases, text files, images, video, music, and more are the variety sources.
• Velocity: The speed in which the data is captured. Consider the fact that there are 300 million photos posted to Facebook each day, 5 new profiles created each minute, and over 293,000 status updates are posted every sixty seconds. Being able to weed through all of the data and only select the important pieces -- quickly -- is velocity.
Big data can come from a variety of sources, ranging from customer data, social media data, or the Internet of Things (such as GPS navigation, cars, home automation, and more). It is capable of producing information about just about every aspect of your customer's life in the form of a data trail, and if analyzed correctly, can lead to a better understanding of their lifestyle and purchasing habits. Or in simple words we can say “Big Data includes data sets whose size is beyond the ability of traditional software tools to capture, manage, and process the data in a reasonable time.”
As companies grow and become more data-driven, these insights will become more important to not only business strategies, but operational efficiency. Big data gives companies the opportunity to collect much more in-depth market and customer intelligence, giving them the information they need to provide much more in-depth analysis of their target audience.
Everyday business transactions will benefit from big data. For example, insurance companies are capable of detecting a potential fraudulent claim by analyzing the claim to verify if it can be automatically reviewed and approved or flagged for review by a specialist.
Needless to say, if your business has a website, a social media presence, or even accepts credit cards, it collects data on its customers. The data collected can range from location, name of the customer, where they found your website, or what they did on it. Because of this, companies need to have a strategy set in place to record this information and analyze it to improve their services.
Everyday business transactions will benefit from big data. For example, insurance companies are capable of detecting a potential fraudulent claim by analyzing the claim to verify if it can be automatically reviewed and approved or flagged for review by a specialist.
Needless to say, if your business has a website, a social media presence, or even accepts credit cards, it collects data on its customers. The data collected can range from location, name of the customer, where they found your website, or what they did on it. Because of this, companies need to have a strategy set in place to record this information and analyze it to improve their services.
There needs to be a mechanism in place to regulate, monitor, and govern the value creation efforts of the IT systems. This governance mechanism of IT systems deals with the performance and risk management of those IT systems in a manner that would create value for the organizations and ensure that the intended alignment of the IT and business objectives is on track. Hence, IT governance deals with identification, establishment, and linking of the mechanisms of the IT systems to both manage risks and at the same time ensure that their performance is in tune with the stated objectives.
IT governance includes all the key stakeholders in the organization starting with the executive management and the boards and including the staff, customers, and ending with the regulators and investors.
To get best level of maturity in Information Security, Risk & Compliance solutions following services and certification can considered.
IT Governance & Managed Security Services
Risk Assessments & Risk Management
Customized compliance Solutions
COBIT 5 consulting
ITIL consulting & training
Independent Internal Audits
ISO 27001:2013 consulting & maintenance
GDPR consulting & maintenance
Information Security Policies & Procedures
IT governance includes all the key stakeholders in the organization starting with the executive management and the boards and including the staff, customers, and ending with the regulators and investors.
To get best level of maturity in Information Security, Risk & Compliance solutions following services and certification can considered.
IT Governance & Managed Security Services
Risk Assessments & Risk Management
Customized compliance Solutions
COBIT 5 consulting
ITIL consulting & training
Independent Internal Audits
ISO 27001:2013 consulting & maintenance
GDPR consulting & maintenance
Information Security Policies & Procedures
