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The industrial revolution of the 1800s established the building blocks of Manufacturing as we know it today. Man, Machine, Material and Method were connected together to form an intricate system on which manufacturing processes and its operational dynamics were based. The resulting complexity of such a system however, has resulted in ineptitudes which have become difficult to circumvent.  The significance of each element of the 4M’s and the consequent manner in which they mesh together generates a multifarious effect in daily industrial operations. The effect as such can be amounted to the ‘Cascade Effect’ phenomenon, racking through operations and leaving colossal ineffectiveness if left unchecked.

Examples of such inadequacies are:

  • A shortage of resources to ensure smooth operation of a production line amounting to an inability to meet forecasted production requirements
  • Inefficient machinery causing material wastage and a profligate deviation from production plan
  • Over-production due to an inventory surplus in raw and packaging resources
  • Greater incurred inventory costs owing to raw material wastage at line changeovers
  • Imprecise demand forecasting contributing to surplus or deficient stocking

The organizational scrutiny today rests in better demand forecasting and inventory management measures. However from an industrial viewpoint these solutions appear irrelevant and a greater onus is warranted on the problems at hand. A deeper analysis of process functioning in a factory appears necessary to uncover the underlying sources for the inefficiencies.  Reinforcing design of appropriate metrics from first principles and then utilizing them to gain insight on system dynamics remains a priority.  

Addressing the ‘5th M of Manufacturing’ or ‘METRIC’ design is what manufacturers today are turning toward to optimizing manufacturing process and ROI. The design of appropriate Metrics is an important superimposing factor to the 4M’s enabling manufacturers to draw the comparison to KPI standards. Today’s technological prowess ensures the systems and software are in place to capture detailed metrics in real-time.

Factory metrics may involve:

  • Man: Number of available resources, efficiency, level of training, error count
  • Machine: Rate of production, number of tasks the line can handle, lead time, breakdown rate
  • Material: Inventory numbers, Raw material levels, quality of obtained materials, set size, surplus/waste materials, shelf life
  • Method: Demand forecast precision, adherence to production plan, production output size

The use of metrics enables the establishment of quality benchmarking, and other protocols such as supply chain analytics and predictive analytics, root cause analysis and process optimization whilst identifying inefficient driving factors and their remedial measures. Analytics practices such as predictive modeling and simulation, are being extensively used today to target potential scenarios in which inefficient drivers appear. These analyses employ the right analytical approach consisting of maths, business and technology to isolate the most relevant drivers in a manufacturer’s factory operations.

When institutionalized across the factory and manufacturing facilities, data-driven decision making using factory specific data, facilitates several benefits:- operational cost reduction opportunities, inventory level optimization avenues, efficient resource management and overall improvements in the manufacturing process, allowing companies to seize the highest levels of manufacturing perfection.

Special thanks to Guruprasad Shrinivasen and Arun Prasad Raman from Mu Sigma for providing their inputs.  

Views: 16669

Tags: Analytics, Manufacturing, Supply-chain, modeling, predictive


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