Quality (philosophy)

Macroeconomics

Control (management)

Process (computing)

Engineering

Philosophy

Injury prevention

Operating system

Economics

Computer science

Manufacturing engineering

Environmental health

Mechanical engineering

Poison control

CTQ tree

Scrap

Epistemology

Industrial engineering

Artificial intelligence

Six Sigma

Domestic violence

Medicine

Artificial neural network

Lean manufacturing

Production (economics)

DMAIC

Sustainability

One of the common problems of organizations with turn-key projects is the high scrap rate. There exist such traditional methods as Lean Six Sigma (LSS) and DMAIC tools that analyze causes and suggest solutions. New emerging intelligent technologies should influence these methods and tools as they affect many areas of our life. The purpose of this paper is to present the innovative Small Mixed Batches (SMB). The standard set of LSS tools is extended by intelligent technologies such as artificial neural networks (ANN) and machine learning. The proposed method uses the data-driven quality strategy to improve the turning process at the bakery machine manufacturer. The case study shows the step-by-step DMAIC procedure of critical to quality (CTQ) characteristics improvement. Findings from the data analysis lead to a change of measurement instrument, training of operators, and lathe machine set-up correction. However, the scrap rate did not decrease significantly. Therefore the advanced mathematical model based on ANN was built. This model predicts the CTQ characteristics from the inspection certificate of the input material. The prediction model is a part of a newly designed process control scheme using machine learning algorithms to reduce the variability even for input material with different properties from new suppliers. Further research will be focused on the validation of the proposed control scheme, and acquired experiences will be used to support business sustainability.

Innovative Methods for Small Mixed Batches Production System Improvement: The Case of a Bakery Machine Manufacturer