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Industry 4.0

The fourth wave of the industrial revolution is here.

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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 readiness

    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.

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    Industry 4.0 maturity model

    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.

    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 time frames
    • Expensive and time consuming prototyping techniques

    Robotic automation

    • No change from traditional production processes
    • Manual labor intensive

    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 fata 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 (M2M) interactions occur
    • Human error a problem

    Mobility

    • Trial size of innovative products integrated
    • Minimal M2M 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

    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

    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 firmwide
    • 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 time frames

    Robotic automation

    • Robots perform most warehousing tasks
    • Few human errors

    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 firmwide
    • 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

    • Firmwide digitalized prototyping technologies
    • Responsive to customer requirements

    Robotic automation

    Full utilization of robotics in warehousing

    No human error

    State-of-the-art inventory tracking