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Uncovering your "hidden factory"

Aug. 17, 2017

The "hidden factory" runs in a parallel universe, sapping resources. 

Most manufacturers have a “hidden factory” running in a parallel universe to the one they work in every day. “Hidden factory” refers to activities in a manufacturing operation such as workarounds, rework or other wastes, all of which can be a substantial drain on the bottom
line, top line, on employees and, most importantly, on the customer. Many manufacturers would not want to reveal how their product or service is created in their hidden factory, given its inefficient processes and wasteful operations.

Beyond the basic benefits of exposing the hidden factory within your operations (labor and part-cost reduction), the biggest motivation may be the opportunity to gain untapped capacity. The quality guru Armand Feigenbaum estimated loss within the hidden factory could be as much as 40 percent of total company effort.

Many manufacturers may desire to increase throughput and revenues, but are hesitant to invest in new equipment, expand their factory footprint or add a second shift. The best
solution is to release the untapped capacity held within the hidden factory. A good place to start is measuring and optimizing OEE (Overall Equipment Effectiveness), a composite metric that is the product of availability, performance and quality. OEE can be measured for manufacturing cells, lines or plant-wide.

Identifying information-value loops

Value Stream Mapping (VSM) is a popular tool from the lean toolkit. VSM advocates mapping of both material and information flows. Most lean practitioners will confess that most, if not all, of the VSM attention is devoted to material-flow mapping, while the information flows get little attention. The necessity to give the information flows more attention is amplified by the maturity and convergence of new information-technology solutions now available under the umbrella of Industry 4.0 or Smart Manufacturing. Thinking explicitly about Information Value Loops (IVLs) throughout your factory floor is a modern upgrade to the old VSM approach.

IVLs represent the visualization of the five core functions of converting data into useful information for factory-floor situation assessment, problem-solving and decision-making. The Holy Grail is real-time, closed loop IVLs. While real-time, closed IVLs can be very aspirational, a realistic goal is to take minutes, hours and even days out of the IVL cycle time.

Revisiting OEE may provide a good example. Let’s assume that machine performance is the primary pain point. It could be that cycle-time performance, short stops or another root cause is contributing to the shortfall in availability-versus-plan. Step one is to identify the IVL functions associated with assessing, problem-solving and decision-making relative to the machining cell in question. Collection of cycle counts and downtime reason codes can be done manually at the end of each shift. If a network with HMIs does not exist on the floor, communication can be via personal transfer to a front office administrator. Aggregation can be done in Excel. Analysis can be completed manually, ad-hoc at the daily production meeting and action taken via feedback to the cell operator with a day’s lag time. This serves as a baseline from which to improve.

Revealing the hidden factory with smart-manufacturing technology

There are many smart-manufacturing technologies that can enable information value drivers inherent in IVLs. These drivers include:

  • Volume—megabytes vs. kilobytes
  • Velocity—near real-time vs. batch
  • Variety—mixed data types vs. structured data only
  • Veracity—trustworthy vs. questionable

Implementing machine-monitoring devices, electronic work-order routing, ERP software systems or other technologies may improve some or all of these four information value drivers, accelerate IVLs, improve OEE and uncover available capacity disguised within the hidden factory. Essentially, the IVL identification process serves as a requirement analysis for any new IT solutions necessary.