Industry 4.0
The fourth wave of the industrial revolution is here.
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Industry 4.0 maturity assessment: optimizing technology to maximize benefit
Industry 4.0 is changing the manufacturing sector in terms of better transparency and agility, responsiveness to customer needs and cost savings.
Industry 4.0 Maturity Model
The key objective of Industry 4.0 is to develop manufacturing to be faster, more efficient, and customer-centric while pushing beyond automation and optimization to discover new business opportunities and models.
Manufacturing is now happening through intelligent connectivity between machines and technology, enabling manufacturers to make better, faster decisions, optimize production, and save time and money.
Baker Tilly can increase your understanding of how Industry 4.0 can transform your business and improve your competitive advantage. Let's start with gauging your industry 4.0 readiness.
To describe our view on Industry 4.0, we've created the following maturity model that defines five maturity stages a company can be in and key functional areas the manufacturing organizations typically employ.
Level 1
Undefined / Undeveloped
Software Integration: Incompatible software systems. No data transfers between systems. Heavy reliance on manual labor.
Business Strategy: No plans/motivation to invest and adapt to advanced production techniques. Unclear on requirements and direction.
Data Management: Minimal capture and storage of large data. Unorganized data storage, hard to access and utilize.
Big Data Analytics: Data analytics have minimal use in the value chain. Do not impact processes and offer no value to decision-makers. Limited visibility through KPIs.
Production Technology Integration: No automated exchange of data between machines. Minimal use of innovative products. Many occurrences of human error.
Mobility: No investments to allow production data to be visible in the mobile world. Must be at the source to gain visibility.
Product Development: Extended design to market timeframes. Expensive and time consuming prototyping techniques.
Robotic Automation: No change from traditional production processes. Manual labor intensive.
Level 2
Repeatable
Software Integration: Some basic systems are integrated. Plans in place to invest in further integration. Mostly relies on manual data transfers.
Business Strategy: Benefits of digitalization being realized. Motivation to adapt is being cultivated. Digitalization requirements are being realized.
Data Management: Some data captured in effective ways. Plans to expand data capture and storage becoming an area of interest. Cloud technology starting to be utilized. Less manual labor required.
Big Data Analytics: Big Data analytic packages beginning to impact decision making, more employees trained to use. Goals to further utilize analytics in production set. KPIs tracking efficiency.
Production Technology Integration: Trial size of innovative products integrated. Minimal Machine-to-Machine interactions occur. Human error a problem.
Mobility: Trial size of innovative products integrated. Minimal Machine-to-Machine interactions occur. Human error a problem.
Product Development: Low customer responsiveness. Little experience with digital modeling.
Robotic Automation: Machines capable of simple automation. High probability of human error.
Level 3
Defined & Integrated
Software Integration: Most software systems integrated. Integration plans are being put into action.
Business Strategy: Vision of future state beginning to take form. Management establish goals and determine enterprise requirements. Culture shifting to accommodate changes.
Data Management: Implementing advanced data capture systems. Expanding scale of implementation of cloud storage and integrated technology on shop floor. Employees utilizing new data.
Big Data Analytics: Analytics important to decision modelling. Large understanding of usage. Moderate range of KPIs, efficiency problems highlighted and trends noticed.
Production Technology Integration: Intermediate amount of devices integrated. M2M communication established. Sensors, wearable devices in some areas. Noticeable reduction in human error.
Mobility: Some systems have mobile platforms established. Intermediate amount of data accessible on mobile devices. Employees trained in mobile platforms. Visibility increases.
Product Development: Some systems have mobile platforms established. Intermediate amount of data accessible on mobile devices. Employees trained in mobile platforms. Visibility increases.
Robotic Automation: Introduction of minor robotic automation. Processes/ inventory tracking require machine-human interaction.
Level 4
Measured & Managed
Software Integration: Data flowing throughout most areas of the enterprise. Investments are beginning to show returns.
Business Strategy: Management has established and is aware of digitalization strategy. Investments are budgeted. Progress benchmarks are established.
Data Management: Integrated technology systems have spread throughout most of the enterprise. Cloud data is accessible to relevant users. Data is being applied to improve operating systems.
Big Data Analytics: Accessible and easy to compile data analytics nearly firm-wide. KPIs are essential to production decisions. Trends become large points of reference.
Production Technology Integration: Innovative technology in many areas; sensors, wearables. M2M communication covers most of shop floor. Greatly improved efficiency. Large reduction in human error.
Mobility: Mobile software compatible with many devices. Most data is accessible on mobile devices. Employees have a deep understanding of platforms. High level of visibility off site.
Product Development: Large investments in Digital-to-Physical techniques. Product to market in reasonable timeframes.
Robotic Automation: Robots perform most warehousing tasks. Few human errors.
Level 5
Optimized
Software Integration: Complete software integration throughout entire enterprise. Optimal level of compatibility between systems in all areas of business.
Business Strategy: Culture adjusted for digital shift. Requirements are clear and defined. Timetables and budget are established.
Data Management: Complete integration of data capture systems. Cloud data is organized and easy to access firm-wide. No manual labor required. Data is shaping decision making.
Big Data Analytics: Data analytics are essential through-out value-chain. Historical trends captured and displayed. Wide-range of KPIs available. Clear, concise diagrams accessible.
Production Technology Integration: Smart Factory status. Interoperability across all machines. No human error. Optimized efficiency.
Mobility: Completely integrated mobile functions. Data accessible on all major mobile platforms. Complete off-site visibility.
Product Development: Firm-wide digitalized prototyping technologies. Responsive to customer requirements.
Robotic Automation: Full utilization of robotics in warehousing. No human error. State of the art inventory tracking.