Daydreaming factories

Optimisation of factories, a cornerstone of production engineering for the past half century, relies on formulating the challenges with limited degrees of freedom. In this paper, technological advances are reviewed to propose a “daydreaming” framework for factories that use their cognitive capacity for looking into the future or “foresighting”. Assessing and learning from the possible eventualities enable breakthroughs with many degrees of freedom and make daydreaming factories antifragile. In these factories with augmented and reciprocal learning and foresighting processes, revolutionary reactions to external and internal stimuli are unnecessary and industrial co-evolution of people, processes and products will replace industrial revolutions

Determination of machinability considering degradation of accuracy over machine tool life cycle

AbstractThe emergence of financially an environmentally conscious manufacturing has resulted in a need for efficient process planning in today's manufacturing system. Process planning based on nominal machine tool specifications, limits predictive capabilities with regard to the final part quality. More efficient process plans can be achieved once an accurate machine tool capability profile has been defined. Machine tool capability profiles deliver up-to-date resource attributes such as availability, health and applicability into the process-planning stage. A manufacturing resource's health degrades continuously throughout its life cycle due to environmental factors, part wear, operator competence, etc. Identifying and compensating for these factors during process planning may alleviate material wastage and machining estimate production time and cost via decision-making mechanisms. In this paper, the STEP-NC Standard is used to represent a model of machining resources, including worktable, spindle and tool status during a machine tool's operational lifespan. A prototype of machine tool capability profile enabled process planning system is then presented and tested to highlight the advantages of this approach

A STEP-compliant method for manufacturing knowledge capture

AbstractOver the last 50 years the development of CNC machines has seen a plethora of part programming languages. These programming languages have provided major barriers for the interoperability of information between CNC machines and Computer-aided (CAx) systems. Thus the process knowledge in existing part programs cannot easily be recycled and reused, due to an inability to interpret these forms of data. In fact, the process knowledge in the existing part programs is vital to develop process plans for new products, reduce leading time, and accumulate knowledge to enhance the product quality based on previous knowledge. In this paper, a STEP standard compliant method is proposed to recycle manufacturing knowledge from shopfloor in a universal manner. An EXPRESS model of CNC programming languages has been developed, though which different programing dialects can be translated into neutral data model. Based on the neutral data, a process comprehension method was used to capture process knowledge from CNC part programs and represent the knowledge in a standardised format. The EXPRESS model also forms a basis for a comprehensive machine tool modelling to assistant process planning activities. The proposed method is implemented in a prototype system and an industrial inspired component is used to validate the knowledge capture method