Polyhedrika

  Design of experiments, is a systematic experimentation, with a process critical factors, in order to correlate these factors to process responses. In DOE with Excel we obtained a linear relationship, between several factors and one response.  In Response Surface DOE  this was extended to non-linear relations. In both cases we were optimizing one single response. Now we will analyse some cases where more than one response needs to be optimized. Problem Description Download file Multiple Response.xlsm from OneDrive to your PC. We want to maximize yield and minimize cost in a process where we have identified three critical factors which may affect both. These are the factors and levels we want to experiment with: Full Factorial DOE We start with a full factorial with two central points DOE and run a simulation of the experiments in sheet YieldCost Simul  we then add the interaction columns (green headers) for the analysis: We now use Excel Data Analysis > ...

System constraints are key when it comes to optimizing our value stream. The process bottleneck limits the overall throughput and it determines such things as manufacturing lot sizes. Learning by doing is an effective way to understand how a value stream works. With this simple manufacturing line simulation you can experience the effects of alternative solutions in order to maximize profit.  When resources are shared by several products there is a setup time when changing product and you have to decide what is the optimal production lot size to optimize the process. Download this Excel file TOCeng5.xlsm from OneDrive folder Polyhedrika Close other Excel files before you open this one and enable Macros. Process Objective Run the simulator to obtain the maximum profit after one simulated week. You have an initial capital of 1000 € which you can use to buy materials to feed the blue, green and brown machines. Fixed expenses amount to 2000 €/ week and they will be subtracted from th...

  The Theory of Constraints is a process improvement methodology that emphasizes the importance of identifying the " system constraint " or bottleneck. By leveraging this constraint, organizations can achieve their financial goals while delivering on-time-in-full to customers, avoiding stock-outs in the supply chain, reducing lead time, etc. Manufacturing Process Example With this simple value stream above, to produce products A and B, we want to illustrate the way to maximize profit taking into account the system constraints . Each product is made by assembling two sub assemblies, one of them common to both products. The process consists of three sequential operations for which there are special purpose workstations with a corresponding operator each trained for the specific job: Manufacturing Test Assembly We want to know how many products A and how many B we should produce to maximize profit. System Constraints Product Margin We want to maximize overall profit so we calcu...