Strategies for Developing Granular Cost Analysis

10 Mar 2020 at 23:00
Documenting the true cost of production for any product is a key step in understanding profitability, but in facilities producing a high mix of product can be hard to associate costs with a specific production run. As a result, averaging is commonly used to associate electrical costs, machine costs and labor with a specific product. Moving from averaging to a more accurate cost analysis gives product management better insight into costs which allows for better pricing models and long term a better understanding of the business.

Documenting the true cost of production for any product is a key step in understanding profitability, but in facilities producing a high mix of product can be hard to associate costs with a specific production run. As a result, averaging is commonly used to associate electrical costs, machine costs and labor with a specific product. Moving from averaging to a more accurate cost analysis gives product management better insight into costs which allows for better pricing models and long term a better understanding of the business.

 

Automation is key to developing any KPI

KPI’s based on manual entry are prone to errors and the possibility of abandoning the manual tasks. Automated measurements eliminate any impact on the work force. Creating a database of periodic measurements allows for historical analysis which can lead to insights only visible over a longer measurement cycle. The top four challenges to developing an automated product production cost analysis are:

Documenting the amount of consumable product used during the manufacturing of a specific product and documenting any scrap of raw material

Mapping power usage to the specific product being run at the time of measurement

Documenting any product scrapped during production

Documenting the total number of shipable units produced for a specific product batch

 

All manufacturing processes start with raw materials

These materials include anything the manufacturing facility uses as an input. Ingredients for a specific batch can be pulled together in a manual or automated process but at some point a machine is used to combine the ingredients. This machine represents the start of the process and can be used to document the use of consumable product. The current state of the machine can be read automatically from either a PLC or an HMI. Additionally, any weighing of ingredients with electronic scales can easily be captured automatically. HMS can convert virtually any machine with a Ethernet port, Serial port or an HMS into a data source.

The Koss Industrial mixer is can easily be connected to a monitoring system to count the number of jobs executed each day. Batch info can be used to associate the mix with a specific product being produced.

The number of machines that can be integrated into a automated process monitoring system is almost unlimited. Here is a list of vendors leveraging PLC’s to create food production systems. All of these systems can be monitored automatically using the HMS Networks Flexy gateway.

 

 Mixers/Grinders    

 Extruders     

 Ovens    

 Oven Drying    

 Packaging   

  FPEC Corp.    

  Extru-Tech 

  Lanly 

  Amisy 

  Tetra Pak 

  Eirich Machines   

  Coperion 

  Sveba Dahlen 

  Kreyenborg    

  Buhler AG 

  Ross Syscon    

  Frain Industries 

  Revent International    

  DST Seibu Giken           

  Marel HF 

  Sterling Systems & Controls   

  Readco Kurimoto 

  Formcook 

  Devex 

  Middleby Corp.           

  Mepaco

  Specialty Food

  Process Technologies    

  Haas Food Equipment         

  Ventilex 

  JBT Corp 

 

 

Investing in your data

Manufacturers producing 1000 or 10,000 units per month may struggle to justify an investment in a quality improvement program. Bring in a consulting company to analyze operations is an option, but the costs are typically beyond the reach of most relatively low margin food and beverage production facilities.

 

HMS Networks and Altizon have developed a path to manufacturing optimization that pays for itself. The solution is an incremental approach to process improvement that produces results based on a very limited investment and then can be easily scaled to achieve further benefits. The solution is based on three key tenets:

Process Visibility leads to process improvement across the organization

Measurable KPIs shall be based on machine/sensor data to eliminate ambiguity

Granular cost analysis vs daily or monthly cost averaging leads to lower production costs

 

Manufacturing Optimization Solution

Altizon and HMS Networks both recognize that small to mid-size manufactures do not have the time or budget to completely overhaul their manufacturing processes. HMS and Altizon have developed a system called First Line Analysis. The outcome of this First Line Analysis is a fully functional process optimization system for a single line.

 

This solution involves instrumenting a single line with data collection gateways from HMS Networks. Then passing that data to Altizon for organization, storage and visualization. The solution offers the end user all of the benefits of a complete manufacturing optimization solution on a single line. The manufacturer can expose the platform to their entire team and measure the results of the solution by fully optimizing the line. The results can then be used to justify further investment across the organization.

 

Time is money so Altizon and HMS Networks have developed an engagement model for our First Line Analysis that limits the time investment required on the manufacturer side less than 40 hours (including all planning meetings, gateway installation and training). A typical First Line Project can be completed in less than 30 days.

 

Lets get started with a free manufacturing optimization evaluation!

Manufacturing Optimization Evaluation