Steve Beeler

You have a goal…I have a way to get you there.

Continuous Improvement

A Plan for Every Part

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A manufacturing marketplace organized through A Plan for Every PartA Plan for Every Part drives waste out of inventory and warehousing operations.  It is the foundation for the continuous improvement of your procurement and material handling activities.  Here’s how to get started:

A Plan for Every Part is exactly as named: a compilation of facts and figures about all of your part numbers.  While there is specialized software for this purpose, an Excel spreadsheet works fine, too, in many situations.

Typical dimensions include:

  • Part number
  • Part description
  • Supplier
  • Annual usage
  • Supplier
  • Container type
  • Container size (length x width x height)
  • Part Weight
  • Container capacity
  • Storage method
  • Location
  • Transport method

Compiling all of this data is messy and people intensive.  Designing a data collection template for each part will increase accuracy, standardize units of measure, and generally speed things along.  A change process will be needed to maintain the integrity of the data.

As this database takes shape, opportunities to reduce complexity (and subsequent waste) in containers, racks, and material handling equipment will appear.  There are great benefits in standardization!  Defined locations improve inventory control and reduce if not eliminate the time wasted looking for parts.  An overall reduction in inventory can also be expected through less overproduction and increased inventory turns.

Set up length, width, and height as separate fields so that they can be sorted separately.  Ask me how I know this.  🙂

There may be a temptation to limit A Plant for Every Part to the highest usage or most expensive parts.  Don’t go there.  Any part, even a small bolt, can halt production if it is missing when needed.

Thinking about warehouse automation?  A Plan for Every Part is a necessary prerequisite.

Market Place Design Checklist incorporating A Plan For Every Part

On my capacity expansion project, we are combining A Plan for Every Part with this material handling checklist to design and size the new plant’s marketplaces.  Not only will the marketplaces be better both operationally and financially today, but we are building a bridge to automation opportunities tomorrow.

 

Business Process Mapping

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Business process mapping answers the who, where, when, and how questions about what actually happens inside your company. They can range from relatively narrow questions (how are credit applications approved?) to more comprehensive questions (how is a customer enquiry turned into a factory work order?)

business process mapping

While a business process can be complicated, business process mapping itself is straightforward. Here’s how:

Only three elements are required:

(1) A box captures a process step. A typical business process will have dozens or more steps from start to finish. Write process steps in a “do something” format (“Review Credit Application”).

(2) A diamond captures a decision point. They are often written as questions (“Credit Approved?” or “OK?”). Yes goes one way, no goes another. Diamonds are very important as they are often the start of rework loops. In our credit approval example, an incomplete credit application (a quality defect) will have to be sent back for missing information, a waste of both time and money.

(3) A triangle captures inventory. In our credit approval example, there is a queue of applications (electronic or paper) ahead of the analyst. Where inventory collects in a business process is a great clue as to where the constraint (bottleneck) resides. Break the bottleneck, and the throughput of the entire business process is improved.

Connect these elements in process logic and you have a business process map. A brainstorm session with sticky notes on a white board is a great way to get started. Map your existing process first. Take a picture with your cell phone…this is your current state process. Now for the continuous improvement. Experiment (move things around, add or delete steps, change approval authorizations, change acceptance levels, etc) until you have a nimble and robust business process.

As an example of business process mapping, here is a redacted portion of the upstream “sales funnel” for a manufacturer of custom products:

Sales Funnel map

Business process mapping is a great training aide. There is no better way to visualize how a new employee’s roles and responsibilities fit into the bigger picture.

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Manufacturing Plan Verification

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Our dynamic economy is characterized by constant change. New products are brought to market, achieve commercial success, and then are made obsolete by something better, faster, cheaper. An essential element in successful product creation is manufacturing plan verification.

A manufacturing plan is a comprehensive compilation of all the facts, figures, and assumptions around making something of commercial value. A plant layout is necessary but not sufficient. How fast must each machine operate? What are the quality requirements? What are the optimum inventory levels? What is the annual volume for these things? How much money is available for investment? What is the unit cost target?

manufacturing plan verification

A manufacturing plan describes a long chain of events from order to delivery. It is not just enough to get each link in the chain to work. The entire system of links must work in harmony to deliver business plan operational and financial metrics. This is not easy to accomplish. Manufacturing plan verification manages this risk.

A robust manufacturing plan starts with business plan objectives which are cascaded down into plant department performance targets through a high-level discrete event simulation model. Next, department performance targets are cascaded down into line level performance targets through a more detailed, line-level discrete event simulation model.

 

Manufacturing Plan Verification

With performance targets in hand, manufacturing teams can confidently do the detailed processing of their link in the chain. Systemic risk has been minimized if not eliminated totally: if each link meets its target, then the chain will work as expected. Manufacturing teams may be working remotely but they are not working in isolation…they are connected through the line-level discrete event simulation.

Before program approval, each manufacturing team reports back on their performance predictions for its link in the chain. These values replace the targets in an integrated discrete event simulation model of the entire manufacturing process. The manufacturing plan is verified when this integrated model meets or exceeds business plan objectives.

In addition to verifying production flows through discrete event simulation, material handling simulation models are often utilized prior to program approval to predict and optimize fork lift requirements, traffic flows and congestion, and indirect labor requirements.

Does simulation lead manufacturing planning or vice versa? A little of both, in a collaborative Plan-Do-Check-Act continuous improvement cycle.

Simulation Output Reports

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Discrete Event Simulation is a portal to the future: find constraints, test strategies to break them, improve performance to the goal, maximize investment returns, and reduce risk. Shown below are three powerful simulation output reports.

Simulation Output Reports

Time in State. Time in state simulation output reports are especially useful in finding the constraint in the process. Before the constraint, machine elements are generally blocked (blue) more than they are starved. After the constraint, they are starved (yellow) more than they are blocked. The machine element with the most uptime (green) is likely the constraint.  Knowledge of the constraint’s location is a key factor in improving the process. Focus on the constraint for opportunities to increase throughput. Look to non-constraints for opportunities to reduce operating costs.

Simulation Output Reports

Volume Histogram. The volume histogram is the first to two methods used to validate a simulation model against its real-world process. How production counts vary over time is an important metric…the less uncertainty the better.  The volume histogram provides a qualitative comparison of the hour-to-hour variation in volume throughput.

Simulation Output Reports

X-bar & R Chart. The production count X-bar & R chart provides a more quantitative comparison between the simulation and the real-world process. Statistical process control charts not only quantify the magnitude of the common cause process variation but also identify special cause events. Characterizing the output variation as common cause vs special cause is an important factor in validating the simulation model. It is difficult if not impossible to simulate special cause events. That is because discrete event simulation “engines” utilize constant probability random number streams. If the real-world process variation is being driven by non-random events, then the root causes of the special cause events will have to be removed before the simulation what-if results will predict future performance.

These three simulation output reports are the foundation for a Plan-Do-Check-Act continuous improvement of the simulated manufacturing or business process. Simulate, validate, and experiment. A robust solution will follow.