AI Improves Production Planning and Factory Scheduling
Supply chains are essentially at the forefront when it comes to machine learning and the use of artificial intelligence (AI). Machine learning has been instrumental in the progress of demand planning and improving forecast accuracy. Forecasts are improved by involving iteration, a mathematical or computational process. Machine learning is part of continuous improvement. In demand planning, machine learning looks at forecast accuracy, and asks itself, if the forecast was changed in some way, could improvement be possible?
Supply chain professionals seek to utilise machine learning and artificial intelligence to develop the field of production planning, which is continuously and dynamically changing. This will be a much more difficult challenge to face compared with demand planning. Production planning applications are used for both daily planning of production and creating weekly or monthly plans to divide the production tasks that need to be accomplished across several factories. When utilised in production planning systems, it allows you to collect essential data and visualise, analyse and then share that data if required. However, there is a need to combine this technology with other processes to develop the most benefit from it.
