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A high level of competition in the food industry, specifically in the Middle East and the UK has forced companies to improve their processes by reducing lead time, waste, and costs and increasing production efficiency. The main challenge to the achievement of the process improvement objectives is the high level of process variability. Therefore, this research investigates the different types of variability in food production system and proposes a methodology to reduce the effect variability in food production system. The proposed methodology integrates process mapping, discrete event…mehr

Produktbeschreibung
A high level of competition in the food industry, specifically in the Middle East and the UK has forced companies to improve their processes by reducing lead time, waste, and costs and increasing production efficiency. The main challenge to the achievement of the process improvement objectives is the high level of process variability. Therefore, this research investigates the different types of variability in food production system and proposes a methodology to reduce the effect variability in food production system. The proposed methodology integrates process mapping, discrete event simulation, Taguchi orthogonal arrays, correlation analysis, and the rule-based system. The integrated method allows quick response, controls the environment without production interruption, reduces the number of experiments and the variability in high variable areas, which narrowed the improvement in the required areas and increased its effectiveness.
Autorenporträt
Expert in Continuous Improvement and Lean Six Sigma. PhD in Manufacturing operations research (De Montfort University, Leicester, UK). MSc in Supply Engineering and Logistics (Warwick University, Coventry, UK). BSc in Industrial Engineering (King Abdulaziz University, Jeddah, Saudi Arabia).