Blog: A product’s life starts when unwrapped and powered on

A product’s life starts when unwrapped and powered on

A traditional manufacturer completes the development cycle of a new product: According to waterfall stage-gate processes R&D will sign off its delivery once the quality has met defined criteria, the product then leaves the labs as manufacturability has been accepted by the factory, and then R&D is off to the next project.
Consequently, the product launched is put on display in the stores, and potential customers may buy it as is. At the manufacturer’s lab an engineering team stays alert for identifying cost savings and fixing problems at the assembly line or in the market.

The traditional after sales cycle

Customers quickly spot the quirky parts and weaknesses. This begs the question why many companies then treat the product as “out of sight out of mind” and discontinue R&D when it hits the customers?
As the automobile industry and others are aware, the value of service and maintenance can constitute a substantial part of the total value during the product’s lifetime. For several years the car industry has tried recapturing the customer’s loyalty by service contracts and among others including updates free of charge to the latest SW releases – the one spare part not available as a cheap OEM variant.
A concrete example of exceptional customer service (yet not very scalable): In Copenhagen, there is a car dealer that as a part of its service rides with customers while listening to their feedback, noting the vehicle’s behaviour, and is eventually able to add sales, besides taking care of the actual service.

The product is never complete

An automated and connected version of the car dealer would be the product itself reporting back daily use from numerous sensors and behavioural data analytics .
A method deployed already in the wind turbine industry, the R&D organisation now embraces lifecycle management of the deployed products. Continuous improvements are implemented and distributed as software updates, once becoming available.
Tesla has the full autonomous driving algorithms performing a ‘shadow mode’ in the background, to gather statistical data to show false positives and false negatives of the software comparing itself to the human driver in all driving situations, eventually to prove it is safer than the human at the steering wheel.

Winning organisations encompass continuous R&D

For a less fancy product than a Tesla examples from industrial and consumer products are similarly changing from “out of sight” to continuous updates:
Industrial components are traditionally tailor-made with exact memory capacity and processing power to fit exactly the purpose from planning inception. The slim-fit design can be traced back to a time where developing dedicated electronics, every bit and byte represented a considerable expense.
Fully customised solutions are as smaller production series too expensive compared to mass-produced standard COTS (commercial-off-the-shelf) platform offering versatility and full tool chain for fast development and deployment.
Adding more processing power and memory than initially assumed necessary thus opens for continued product development and improvements after shipping either by service technicians’ SW updates or automatically Over-The-Air.

Create new IoT services in-market

Smaller IoT systems do not normally undergo an aftersales explosion of added functionality similar to PC’s or smartphones but as runtime and market data are gathered, it may be profitable to upgrade the install base with new subscription features and optimised parameters rather than expecting a resell of entire new products.
As an example, a “SKF Wireless Machine Condition Detector” is magnetically connected to the machinery and measures vibrations. Results are sent to a mobile App using Bluetooth – which means the sensing device itself can be updated with improved algorithms while the smartphone or tablet analyses the results collected. In case the result warrants further evaluation, the data recorded will be sent for expert evaluation at SKF.
Hence the ability to upgrade and improve the product install base may add business value throughout the product lifecycle – besides the greener foot-print from keeping products alive for a longer time span.

More information:

Partner, Fredrik Svensson, Fredrik.svensson@glaze.se, +46 705 08 70 70

Positioning technologies currently applied across industries:

Global Navigational Satellite System: Outdoor positioning requires line-of-sight to satellites, e.g. GPS: the tracking device calculates its position from 4 satellites’ timing signals then transmits to receiving network
–    via local data network, e.g. wifi, proprietary Wide Area Network
–    via public/global data network, e.g. 3G/4G

Active RFID: A local wireless positioning infrastructure built on premises indoor or outdoor calculates the position based on Time of Flight from emitted signal & ID from the tracking device to at least 3 receivers or when passing through a portal. The network is operating in frequency areas such as 2.4 GHz WiFi, 868 MHz, 3.7 GHz (UWB – Ultra Wide Band), the former integrating with existing data network, the latter promising an impressive 0.3 m accuracy. Tracking devices are battery powered.

Passive RFID: Proximity tracking devices are passive tags detected and identified by a reader within close range. Example: Price tags with built-in RFID will set off an alarm if leaving the store. Numerous proprietary systems are on the market. NFC (Near Field Communications) signifies a system where the reader performs the identification by almost touching the tag.

Beacons: Bluetooth Low Energy (BLE) signals sent from a fixed position to a mobile device, which then roughly calculates its proximity based on the fading of the signal strength. For robotic vacuum cleaners an infrared light beacon can be used to guide the vehicle towards the charging station.

Dead Reckoning: Measure via incremental counting of driving wheels’ rotation and steering wheel’s angle. Small variations in sizes of wheel or slip of the surface may introduce an accumulated error, hence this method is often combined with other systems for obtaining an exact re-positioning reset.

Scan and draw map: Laser beam reflections are measured and used for calculating the perimeter of a room and objects. Used for instance when positioning fork-lifts in storage facilities.

Visual recognition: The most advanced degree of vision is required in fully autonomous vehicles using Laser/Radar (Lidar) for recognition of all kinds of object and obstructions. A much simpler method can be used for calculating a position indoor tracking printed 2D barcodes placed at regular intervals in a matrix across the ceiling. An upwards facing camera identifies each pattern and the skewed projection of the viewed angle.

Inertia: A relative movement detection likewise classical gyroscopes in aircrafts now miniaturised to be contained on a chip. From a known starting position and velocity this method measures acceleration as well as rotation in all 3 dimensions which describes any change in movement.

Magnetic field: a digital compass (on chip) can identify the orientation provided no other magnetic signals are causing distortion.

Mix and Improve: Multiple of the listed technologies supplement each other, well-proven or novel, each contributing to precision and robustness of the system. Set a fixpoint via portals or a visual reference to reset dead reckoning & relative movement; supplement satellite signal with known fixpoint: “real time kinematics” refines GPS accuracy to mere centimetres; combine Dead Reckoning and visual recognition of 2D barcodes in the ceiling.

Glaze IoT Cloud Project Process

Beacon Tower is Glaze’s Industrial IoT Cloud Platform that can act as either a stepping stone (Platform-as-a-Service, PaaS) or as an out-of-the-box solution (Software-as-a-Service, SaaS) for collection of IoT-data.

Beacon Tower resides in Microsoft Azure and is designed as a customisable and cost-effective IIoT Cloud Platform that helps simplify deploying, managing, operating, and capturing insights from internet-of things (IoT)-enabled devices. Our customers have the full ownership of their data.

When running it as a PaaS we utilise the design and can run it on our customers’ Azure tenant and customise it fully to their requirements.

Beacon Tower connects to all sensors, PLC, DCS, SCADA, ERP, Historians and MES to gain maximum automation flexibility and ​prevent vendor lock-in.

For more information visit www.beacontower.io or read the PDF.

Edge Computing Categories and Questions

Device:
o Sensors
o Internet connectivity
o Battery consumption
o Field Gateway
o Communication protocols (HTTP, AMQP, MQTT, Gateway)
o Format of the telegrams sent to the cloud (JSON, Avro, etc.)

Data:
o Number of devices & number of signals
o Amount of data to transfer per day
– Event-based or batched or mix
– Transfer rate (every second, minute, hour)
o Device timestamps
– Synchronized timestamps with cloud or not
– Local buffering on device, late and/or repeated data
o Any time-critical notifications / alarms
– Latency expectations for non-time critical data
– Alarms generated by device and/or by cloud platform
o Cloud-to-device messages & commands
o Analytics
– Results from time-series data / Streaming analytics
– Analytics workflows on data, machine learning etc.
– Edge analytics / intelligence

Cost expectations:
o Retention periods (for reporting purposes)
o Aggregation of data, possibilities for cost saving

External integrations:
o Reference data / online data

Administration, rights and access:
o Requirements for multi-tenancy (segregated owners)
o Owners/tenants and operators/technicians
o Administrating access to data, auditing use
o API management, consumption of data, 3rd party integrators

Operation:
o KPI measurements for device
o KPI measurements for cloud platform
o Requirements on operators and SLA’s

User-interfaces and functions:
o Operators/technicians
o Customers/end-users

Glaze Business Innovation and Development Framework (BIDF)

1. Strategy

Creating an IoT Strategy that aligns with the existing company strategy and/or points out any discrepancies that needs to be addressed. The IoT Strategy should pinpoint type of IoT opportunities that should be sought and how they can support the Company delivering on their overall strategies.

2. Ideation

The Ideation phase is an innovative and creative phase where we identify the IoT opportunities within the company. This is done by using existing assets, industry expertise, industry analysis, strategy and IoT expertise to find opportunities for IoT endeavors. This is done in an structured but open-minded and creative setting.

3. Refinement

In Refinement the opportunities are detailed, prioritized and evaluated in a series of steps with the goal of finding a short list of initiatives the company want to pursue. These steps takes strategy, competence, risk level, customer maturity etc into account during prioritization.

4. Valuation

The short list of opportunities are detailed even further and business cases are created for each of them. This will lead to a decision which opportunity to pursue further.

Moving on from the Business Innovation phases to Development activities we focus on taking the minimum possible risk of building the wrong solution by using agile development practices.

5. Exploration

Proof of Concepts carried out in this phase in order to map out technology as well as user-oriented risks. This also refines the budget and thus valuation and business case. Also giving valuable input to baseline system architecture and eco system involvement.

6. Planning

Moving to Planning phase, the most promising business case has been selected and now it is time to plan the Minimal Viable Product (MVP), in terms of timeline, resources and detailed design.

7. Foundation

Implementing the baseline architecture, toolchains and most critical points of the project.

8. Development

Full MVP is developed using these three principles: Start small, don’t over-engineer; Agile software development – late changes welcomed; Continuous delivery – every change is immediately visible.

9. Operations

Operations in an IoT-project is more than just keeping the product alive. It is life-long updates and continous sharpening of features and business model, meaning new ideas are fed back in the Innovation and Development Framework.

Heat map example on a typical business case: