Lean Tech provides consulting services within the following areas:
- Energy and production efficiency: reduce shrinkage and scrap, benchmark consumption and optimizing production processes
- Improving product quality: understand process variation and use Statistical Process Control (SPC) to control critical variation
- Increasing productivity: Improve production flow and machine efficiency (OEE)
- Product development: Improve existing products or develop new, using Experimental design (DOE) and Components of Variation
- Emission control and establishing monitoring program
- Measurement: Determine measurement error and improve measurement systems
- Cost-benefit analysis
- Root cause analysis and problem solving
- Predictive maintenance using statistical process control - SPC
- Time management by spending time on value adding activities
Lean Tech also provide analytical problem-solving training using Lean Six Sigma. The training focuses on practical applications and adjusting the training to fit the participants and their company's need. For more information contact Lean Tech.
By benchmarking theoretical and actual consumption, you can estimate possible savings. Raw material consumption can be reduced by reducing shrinkage and optimizing the production process, see efficiency
If you recover raw material by distillation processes, significant savings can be gained through optimization.
To achieve efficient use of raw materials, you need to control your emissions and waste. Read more about production efficiency.
Start by mapping and benchmarking
today’s consumption: Energy usage per product? Energy required for different process steps? For different machines and equipment?
The more you know about your energy consumption, the easier it is to improve. If you don't have the necessary measurements, you can calculate the theoretical consumption, and start by improving your most energy intensive processes. Here are some efficiency tips. Read more about energy efficiency
To improve quality, it is important to consider all factors that can be significant for product quality. Start with process mapping
to identify variables that can affect product quality.
All processes are subject to variation, which may be classified as random / noise (common cause) or assignable cause variation (special cause). Statistical process control - SPC separate normal and special cause variation and can be used to understand and control variation. More about SPC. More about quality improvement.
To achieve high productivity, you need good flow through the value chain. Multiple independent machines can collaborate to produce the complete product. If a machine has high scrap rate, downtime or run at lower speed, the result is queues and non-balanced processes.
To measure the efficiency of each machine and determine bottlenecks, you can use OEE (Overall Equipment Effectiveness) as an indicator. Productivity can be improved by increasing the efficiency of the slowest machine but increasing the buffer between machines can also help. More about OEE and productivity.
To reduce emission, you need to know the current status and the emission sources. Start by mapping todays’ situation; Quantify your emissions to water, air, landfill and recovery by data collection and sampling. Significant savings can be achieved by reducing emission (Lean Tech has quantified wastage of 1.4 million $ / year at a company by mapping emissions). Lean Tech perform emission mapping
, IPPC (Integrated Pollution Prevention and Control) reports quantifying emissions and waste, and BAT (Best Available Technology) comparison. More about emission control
In Norway, emissions are regulated through the company's discharge permit. The Norwegian Environment Agency requires that Norwegian companies document their emissions to soil, air and water to ensure that they are within the requirements of the permit. In 2010 came a requirement from The Norwegian Environment Agency to establish a monitoring program for emissions to air and water.
Lean Tech helps companies develop complete Monitoring program or part of it, like calculation of uncertainties. More about monitoring program.
Define the right goals and decide how to measure is important to avoid wasting resources and not being able to quantify the effect of your effort. Companies spend a lot of resources on data acquisition, data warehouse, reporting and visualization. What information is important to monitor your process and evaluate your goals? How will you break down overall business objectives to operational targets and process indicators? More about goals and objectives
Today there is access to infinite amounts of data; but what information do you need and is data quality adequate? Spend resources on data quality rather than data quantity. If you don't trust your data, it's worthless. Implementation of comprehensive data acquisition can result in production downtime due to failure with the data collection. More about data application
Data visualization using statistical programs, makes it is easier to see connections and trends between different variables and data sets. Multivariable analysis shows the correlation between the various factors. Are there outliers? Why? Are factors correlated? Positive or negative correlation? Linear or non-linear? Can the correlation be explained? Lean Tech assist with data analysis. More about data visualization
All measurements involve uncertainty. A Measurement System Evaluations (MSE) can address precision, accuracy, sensitivity and capability. By measuring the same item repeatedly, and include factors like analyst, instrument and batch you can detect the contribution to the overall variation of each factor. Read more and see a video about measurement error
With experimental design you can get the information you need with minimal effort. You reduce development costs and save time by testing multiple combinations at the same time.
Good design and proper analysis will help you decide optimal solutions. DOE can be used both when developing new products and when improving existing ones. More about DOE.
When the level of a factor is random, such as raw material batch, reactor, instrument, operator, day, etc., Components of variation (CoV) is more applicable than design of experiment (DOE). While the levels of a DOE are controlled, a CoV determine how much various factors contribute to the overall variation based on their natural variation. More about CoV
To decide between alternative solutions, cost-benefit analysis can help you make the right decision. It can be challenging to quantify the effect. It requires the ability to see the complete picture and how the change affect the overall business. You also need measurements and facts to quantify the effect. The Improve phase of Lean Six Sigma is all about selecting the right solutions. Read more about cost-benefit analysis
The aim of root cause analysis is to identify the factor that resulted in one or more past events. Often the event is unwanted and by identifying the root cause it is possible to prevent the event from happening again. Process mapping
(PM) in combination with a Thought Map
(TM) or A3 to identify possible root causes and structure the problem solving is a good start. More about root cause analysis.
Statistical process control separates normal and special cause variation to respond correct to measurement results, assess stability (predictability) and capability (ability to deliver on customer requirements). It has many applications such as quality control, predictive maintenance, comparing machines and equipment for continuous improvement and to make the right decision when making new investments. It can also determine effect of changes. More about SPC