11 Mar PROCESS OPTIMISATION
Introduction to process optimisations
Processes are only as good as they are designed, documented, implemented and adhered to. But what does the reality often look like? Employees no longer know what to do. There are questions, ambiguities, discussions. Interruptions, malfunctions or accidents occur. Spare parts are not available. Raw material qualities fluctuate. Machine settings have to be adjusted. External conditions take their toll. There are process-related weak points, contamination or logistical problems. The specified quality is not maintained. Plants are run in. They are cleaned and retooled. And in all these examples, the company loses substance and money.
Framework for process optimisation
Process optimisations can be realised within a freely definable framework or in a specific discipline such as logistics. Starting points can be weaknesses, capacity bottlenecks or necessary cost reductions. Increasing economic efficiency can also be the decisive factor for a loss analysis. In some cases, it may make sense to conduct a broader analysis that also reveals conceptual potential. Or a first project is carried out within a limited framework as a case study.
Every analysis requires an understanding of the relevant processes, such as the value stream or the manufacturing process. At the same time, a database is required with which losses that occur can be determined along with their significance (share of total losses). In this context, existing operational data collection is advantageous. If no data are available, they must be collected. A co-decisive discipline is the presentation and visualisation of the relevant data. How can I prepare the key data in such a way that the user has the greatest possible understanding of the effective situation without having to make additional queries and investigations? The data should be as up-to-date as possible.
The goal and direction is to optimise the processes within the specified framework, including their handling and operating. Concrete goals are set for this purpose. Processes, technology, ergonomics and the level of automation are important. Although a lot is also possible under the term “low cost automation”. For limited operations, it can be a good approach to drastically reduce the most important three types of losses for the time being. There are various methodological approaches to this. They range from simple “problem-solving stories” to more complex solution procedures to specific approaches to be able to generate a systematic solution for defined tasks. In addition to the analysis of losses, the identification of relevant causes is a mandatory step in the process. Only then can possible measures be identified, for example in a brainstorming session. The measures are then graphically entered into a matrix with the dimensions costs, realisation time and expected solution share. This helps to select specific measures. They should be implemented with a high priority. In the overall process, as indicated, certain sequences are covered with workshops. Ongoing monitoring of the progress made against the objectives is important.
The field of self-optimising processes lies largely fallow. Many processes could be significantly improved by appropriate controls. Examples: Start-up of production plants. Compensation of production or raw material fluctuations. Compensation of environmental influences such as temperature or humidity, etc. In order to design self-optimising processes, the criteria with which the finished product is assessed are crucial. And the question is how they can be recorded or measured as automatically as possible. However, solutions are also possible in which laboratory analyses or, for example, a tasting including evaluation are integrated. The time factor, however, is relevant. The actual control / regulation can either be defined with known relationships between the factors, or optimised with systematic parameter variations to such an extent that effective regulation is possible.
Without sound project management, process optimisation will not work either. Sensible planning, good communication, implementation, creation of measures and realisation, project control and ongoing monitoring of success are important components of a project. In addition, a high priority as well as a declared will to implement is crucial.
To what extent have losses been detected and eliminated in my value stream? An analysis with actionable findings creates clarity.