# How it Works

The *Factory Profit Optimizer methodology* is based on the principle of the optimal product mix. The following example will help you understand how the *Factory Profit Optimizer* can help you increase profits of your factory using existing manufacturing resources.

The following table list the variables of a fictional factory that sells 4 products. The objective is to find the product mix that generates the most profit using different optimization techniques. We will use a manufacturing period of 40 hours (2400 minutes). There is also a market constraint that limit the quantity of products that can be sold.

Product 1 | Product 2 | Product 3 | Product 4 | |
---|---|---|---|---|

Unit Price | $60 | $130 | $180 | $200 |

Material Costs | $20 | $70 | $90 | $100 |

Gross Profit | $40 |
$60 |
$90 |
$100 |

Max Quantity / week | 100 | 80 | 60 | 50 |

Each product goes through the same 4 workstations, but with a different cycle time.

Product 1 | Product 2 | Product 3 | Product 4 | |
---|---|---|---|---|

Workstation A | 10m | 25m | 30m | 35m |

Workstation B | 10m | 15m | 20m | 25m |

Workstation C | 10m | 10m | 20m | 25m |

Workstation D | 20m | 10m | 20m | 30m |

Total Cycle Time | 50m |
60m |
90m |
115m |

## Method 1: Maximize Gross Profit per Unit

Products with the highest gross profit per unit should be sold before products with a lower gross profit. In this example, priority should be given to Product 4, then Product 3, Product 2 and Product 1.

P1 | P2 | P3 | P4 | Total | |
---|---|---|---|---|---|

Quantity | 2 | - | 21 | 50 | |

Workstation A | 20m | - | 630m | 1750m | 2400m |

Workstation B | 20m | - | 420m | 1250m | 1690m |

Workstation C | 20m | - | 420m | 1250m | 1690m |

Workstation D | 40m | - | 420m | 1500m | 1960m |

Sales | $120 | - | $3,780 | $10,000 | $13,900 |

Cost of Goods Sold | $40 | - | $1,890 | $5,000 | $6,930 |

Gross Profit | $80 |
- |
$1,890 |
$5,000 |
$6,970 |

The method creates a product mix that generates a gross profit of $6,970. The market constraint for Product 4 and a manufacturing bottleneck for workstation A were detected. However, these might not be the true bottlenecks.

## Method 2: Minimize Manufacturing Costs

Manufacturing cost should be minimized. We calculate the cost per minute at the bottleneck to manufacture a product.

Product 1 | Product 2 | Product 3 | Product 4 | |
---|---|---|---|---|

Bottleneck Cost | $1.00/m | $7.00/m | $4.50/m | $3.33/m |

In this example, priority should be given to Product 1, then Product 4, Product 3 and Product 2.

P1 | P2 | P3 | P4 | Total | |
---|---|---|---|---|---|

Quantity | 100 | 1 | - | 13 | |

Workstation A | 1000m | 25m | - | 455m | 1480m |

Workstation B | 1000m | 15m | - | 325m | 1340m |

Workstation C | 1000m | 10m | - | 325m | 1335m |

Workstation D | 2000m | 10m | - | 390m | 2400m |

Sales | $6,000 | $70 | - | $1,300 | $8,730 |

Cost of Goods Sold | $2,000 | $70 | - | $1,300 | $3,370 |

Gross Profit | $4,000 |
$60 |
- |
$1,300 |
$5,360 |

The method creates a product mix that generates a gross profit of $5,360. The market constraint for Product 1 and a manufacturing bottleneck for workstation D were detected. However, these might not be the true bottlenecks.

## Method 3: Maximize Unit Sales

Manufacture the most units possible.

P1 | P2 | P3 | P4 | Total | |
---|---|---|---|---|---|

Quantity | 90 | 60 | - | - | |

Workstation A | 900m | 1500m | - | - | 2400m |

Workstation B | 900m | 900m | - | - | 1800m |

Workstation C | 900m | 600m | - | - | 1500m |

Workstation D | 1800m | 600m | - | - | 2400m |

Sales | $5,400 | $7,800 | - | - | $13,200 |

Cost of Goods Sold | $1,800 | $4,200 | - | - | $6,000 |

Gross Profit | $3,600 |
$3,600 |
- |
- |
$7,200 |

The method creates a product mix that generates a gross profit of $7,200. Manufacturing bottlenecks for workstation A and D were detected. However, these might not be the true bottlenecks.

## Method 4: Maximize Profits at the bottleneck

Gross profits should be maximized. We calculate the gross profit per minute at the bottleneck.

Product 1 | Product 2 | Product 3 | Product 4 | |
---|---|---|---|---|

Bottleneck Profit | $2.00/m | $2.40/m | $3.00/m | $2.86/m |

In this example, priority should be given to Product 3, then Product 4, Product 2 and Product 1.

P1 | P2 | P3 | P4 | Total | |
---|---|---|---|---|---|

Quantity | - | - | 60 | 17 | |

Workstation A | - | - | 1800m | 595m | 2395m |

Workstation B | - | - | 1200m | 425m | 1625m |

Workstation C | - | - | 1200m | 425m | 1625m |

Workstation D | - | - | 1200m | 510m | 1710m |

Sales | - | - | $10,800 | $3,400 | $14,200 |

Cost of Goods Sold | - | - | $5,400 | $1,700 | $7,100 |

Gross Profit | - |
- |
$5,400 |
$1,700 |
$7,100 |

The method creates a product mix that generates a gross profit of $7,100. The market constraint for Product 3 and a manufacturing bottleneck for workstation A were detected. However, these might not be the true bottlenecks.

## Method 5: Optimal Product Mix using *Factory Profit Optimizer*

A gross profit of $7,200 was reached using one the previous methods. Regardless of which method is chosen, none have came up with an optimal product mix that will generate the maximum of profits. The best way to find it is to reformulate this example as a mathematical equation. The formula for the gross profit is:

P1⋅$40 + P2⋅$60 + P3⋅$90 + P4⋅$100 = Gross Profit

where contraints are:

- P1 ≤ 100 units
- P2 ≤ 80 units
- P3 ≤ 60 units
- P4 ≤ 50 units
- P1⋅10m + P2⋅25m + P3⋅30m + P4⋅35m ≤ 2400 minutes
- P1⋅10m + P2⋅15m + P3⋅20m + P4⋅25m ≤ 2400 minutes
- P1⋅10m + P2⋅10m + P3⋅20m + P4⋅25m ≤ 2400 minutes
- P1⋅20m + P2⋅10m + P3⋅20m + P4⋅30m ≤ 2400 minutes

We need to find the maximum gross profit that can be achieved while respecting the constraints. The *Factory Profit Optimizer* methodology does not require you to come up with this kind of equations. Everything is done behind the scene.

The *Factory Profit Optimizer* methodology will find an optimal solution quickly by trying thousand of combinations.

P1 | P2 | P3 | P4 | Total | |
---|---|---|---|---|---|

Quantity | 60 | - | 60 | - | |

Workstation A | 600m | - | 1800m | - | 2400m |

Workstation B | 600m | - | 1200m | - | 1800m |

Workstation C | 600m | - | 1200m | - | 1800m |

Workstation D | 1200m | - | 1200m | - | 2400m |

Sales | $3,600 | - | $10,800 | - | $14,200 |

Cost of Goods Sold | $1,200 | - | $5,400 | 0 | $6,600 |

Gross Profit | $2,400 |
- |
$5,400 |
- |
$7,800 |

The *Factory Profit Optimizer* creates a product mix that generates a gross profit of $7,800. The market constraint for Product 3 and manufacturing bottleneck for workstation A and D were detected, which are the true bottlenecks.

This is a simple example with only 4 small processes, yet the *Factory Profit Optimizer* was able to generate significantly more profit than the other methods. The *Factory Profit Optimizer* will be even more useful in real life situations when there are a lot more variables to take into account. Has your factory reached its full Profit potential?