Sustainability
Emission | Energy | BAT
Process improvement
Cost | Quality | Time
Data analysis
RCA | Variation | Cost - benefit
Process development
DOE | ANOVA
Services within Process improvement:
Efficient use of raw materials
By benchmarking theoretical and actual consumption, you can estimate possible savings. If they are significant; next step is to reduce the gap. Conduct a benchmarking per product and per process to decide where to focus. The more information you have, the easier it is to identify improvements. Raw material consumption can be reduced by reducing shrinkage and optimizing the production process.
If you recover raw material by distillation processes, significant savings can be gained through optimization. Lean Tech has managed projects where the raw material consumption was reduced by 470 000 $ annual by recovering raw materials.
Shrinkage of raw materials can end up as emission, through wastewater, air emission, waste to landfill or waste for recovery. If you want to reduce the waste, gaining control of your emission is a good start. Lean Tech perform benchmarking and process optimization.
Efficient use of energy
Start by mapping and benchmarking today’s consumption: What is the energy consumption for different products? What about the different processes? How much energy do different machines and equipment utilize?
The more you know about your energy consumption, the easier it is to improve. If you miss the necessary measurements, you can calculate the theoretical consumption. Start by improving your most energy intensive processes.
It can be profitable to invest in flow meters for steam or electricity meters to differentiate the consumption and identify the most energy intensive processes. Lean Tech has helped a company reduce the energy costs with 200 000 $ annual by mapping the consumption and optimizing the effectiveness of the production process. Lean Tech also assist with benchmarking energy consumption.
Six Sigma involves statistical tool to understand variation and identify critical factors. It is important to know the critical factors of your processes to avoid spending time controlling non-important factors. Control of critical factors gives predictable results and satisfied customers if the quality is within the customer specifications. There are examples of companies that have canceled the launch of new product because they have not identified all critical factors for quality. The variation of product quality was unacceptable for the customer. If critical factors are unknown it's difficult to reduce variation.
What are the critical factors of your processes? How do you control their variation?
Tools to improve quality
Lean Tech use the following tools to improve quality:
Lean Tech use the following tools to improve quality:
- Statistical Process Control and capability reveal whether normal or special cause variation is causing quality issues. These types of variation have different improvement strategies.
- Process mapping identifies variables that contribute to variation of product quality.
- Graphical analysis can prove or disprove root causes
- Hypothesis testing can prove or disprove root causes when graphical analyzes are not clear
- Correlation and design of experiment can help you determine optimal factor values.
- Statistical Process Control (Control Chart) monitors variation of critical variables (proven root causes) and ensures correct quality
These tools are used within Lean Six Sigma's problem-solving method DMAIC: Define (understand problem and set goals) - Measure (map current situation) - Analyze (prove root causes) - Improve (solve root causes) - Control (create lasting results).
To achieve high productivity, good flow through the value chain is important. For some manufacturing companies, multiple independent machines might collaborate to produce the complete product.
Some machines produce more scrap, have more down time or run at lower speed. To measure the efficiency of each machine and determine bottlenecks, you can use OEE (Overall Equipment Effectiveness) as a productivity indicator. It reveals loss of production time and capacity.
The available production time is crucial to the OEE calculation and should reflect the time losses you want to highlight. You can learn more in Lean Techs OEE video.
Low OEE may cause subsequent machines to wait - queuing. Obviously, capacity can be increased by increasing the efficiency (OEE) of the slowest machine, but also increasing the buffer between machines can improve productivity.
To assess this, an analysis of stop-causes and time should be performed to calculate the effect of increased buffer. Lean Tech performs such analyzes.
Some companies have manual logging of stops causes. In this case it is important to have clearly defined stop causes to ensure operating personnel selects the same cause regardless of who's at work. It is also important that the stop causes are defined to identify the root cause. As an example, stop causes like "Other" or "Waiting" do not say anything about the root cause. You need to break this stop cause into possible root causes.
If you need help boosting your productivity, contact Lean Tech to hear what we can do for you.
