The super-charged combination of Lean and IoT is already demonstrating staggering advances in waste reduction and profitability. Early adopters are building on returns they’ve already realized by “super-charging” Lean with IoT, a combination that will grow in power as sensor technology becomes more accessible and widespread, making realtime data and events readily available.
However, many Lean practitioners struggle to make a concrete business case for implementation. By applying the Three M‘s of waste, developed by Taiichi Ohno, Toyota’s Assembly Manager in 1945, companies can create a roadmap to reap IoT waste elimination benefits and a framework to exponentially boost efficiency with sensor technology.
The Three M’s — Muda, Muri, Mura
- Muda - Human activity that consumes resources but produces no value.
- Muri - Unnecessary stress on equipment and employees.
- Mura - Waste from uneven flows and imbalances.
Muda — 7 Wastes Eliminated by Lean + IoT
Muda identifies seven distinct facets that detract from customer value that when combined with of IoT sensory technology, can dramatically reduce valueless operational activities in ways not previously possible. This involves:
- Wait Time — Motion sensors can measure the amount of time a product has (or hasn’t) been moved. Manufacturers can configure alerts to warn them if a product has remained untouched for longer than acceptable times. Troubleshooting measures can be automatically launched if a delay could result in a missed target ship date. These systems aren’t limited to shop-floor operations. Disney uses the same technology to reduce queue times at theme park attractions.
- Transportation — GPS coordinates track how far a product moves during an order fulfillment lifecycle. Aggregating this data provides insight into how to optimize order fulfillment when alternative plants and warehouses are available. This can be especially valuable for products whose distribution costs make up a large component of cost of goods sold.
- Inventory Control — Sensors mounted on stock units can link physical inventory to distribution centers using GPS coordinates. This simplifies cycle counting and increases inventory visibility across the supply chain. Consumer products companies can reduce inventory buildup, enhance flexibility and even satisfy customer demand by capturing consumer behavior data with sensors embedded into connected devices.
- Overproduction — Real-time sensors can send a “stop-the-line” message to prevent upstream processes from producing too much inventory too quickly. Production can be automatically restarted when stock levels return to acceptable thresholds. In global manufacturing operations the same algorithms can regulate and control product movements throughout the entire supply chain.
- Motion — Movement sensors applied to key equipment and inventory items collect value chain improvement data. Skilled professionals can then perform cycle time and “spaghetti” analysis to improve facilities layout and optimize distribution routes.
- Defects — Slow and manual quality assurance processes delay quality improvement initiatives. IoT sensors overcome this by detecting products that deviate from the standard physical process flow. Immediate notification of defects helps address problems more quickly increasing customer satisfaction rates.
Muri — Relieve Over-Burdened People and Processes
Overtaxing systems and employees can lead to unnecessary waste. Overburdened equipment wears out faster and must be replaced sooner. Overworked employees results in accidents and other costly mistakes. Identifying and addressing these stress points is crucial to streamlining operations.
Don’t be surprised, however, to find some employees and systems overtaxed simply by reducing muda and increasing overall system throughput. Removing inefficiencies can expose inherent bottlenecks you never noticed before. Sensory technology can help identify and reduce overload conditions.
Biometric devices for employees coupled with other sensors can identify and predict employee fatigue. Many accidents happen as a result of human overwork, so early detection can avoid workplace injuries and accidents.
In order to prevent resource overuse in the value chain, all critical components that could result in a single point of failure require active monitoring. Petroleum companies, for example, transport oil and gas through pipelines across large geographic areas. If pipe pressure exceeds safe levels, the company risks long term damage to the pipe, and possibly even a rupture. A major spill could cost millions in business disruption, EPA fines, and damaged reputation.
Pressure sensors could avoid this risk by sending warning messages to field engineers as soon as they detect an overload condition. Early detection can save money by extending the service life of the pipeline and preventing a disaster.
Teams need to constantly ask, “what indicators of degradation would be helpful to predict likely safety, quality or service issues?” The answer will indicate what type of sensor could capture this data flow.
Mura — Create Flow-through Integration Across the Ecosystem
Mura, the Japanese word for unevenness and variation, can result in fluctuating demand and chaotic system behavior. We want to smooth out the peaks and valleys of effort to achieve a more balanced workflow. Elimination of work in process (WIP) can go a long way to creating balance within any production system.
Instead of “pushing” WIP ahead, design your systems to wait for a “pull” signal before starting the production of the next item. Electronic or visual signals such as kanban can be used to act as a type of organizational pacemaker to regulate flow. As systems evolve, latency tends to creep into trigger thresholds, so you should analyze and tweak pull signals periodically.
Because IoT sensors send data instantaneously with no human interface, they can be programmed to failsafe misinterpreted pull signals. Likewise, they can coordinate complex scenarios of multiple interconnected flows which can’t be integrated any other way.
Leveraging data captured by IoT devices, can reduce costs and more accurately forecast demand. Skilled data scientists can program algorithms that account for weather, fuel prices, market seasonality, supply chain integration, and combined demand signals to enhance the entire global supply chain.
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IoT is a critical component to supercharge your Lean ambitions. Sensory technology is the next iteration of productivity providing opportunities to maximize the scale, frequency, variety and intensity of data and feedback signals available.
Firms that have a roadmap to realize the combined benefits of Lean and IoT will be positioned to shape the future of disruption, rather than merely react.
John Rossman is a managing director at Alvarez & Marsal and author of the book The Amazon Way on IoT: 10 Principles from the World’s Leading Internet of Things Strategies; Lee Maginniss is a managing director Alvarez & Marsal and LEAN Six Sigma Specialist.