Machine Availability Monitoring for Adaptive Holistic Scheduling: A Conceptual Framework for Mass Customization

Abstract

Although the market started expressing the need for high product variety three decades ago, manufacturing systems have not kept the pace with these social and economic developments. Modern industrial shop-floors are highly affected by the ever-increasing product variety and volatile market demands introduced by the currently established mass customization paradigm. The increasing complexity and high unpredictability in manufacturing activities require immediate reactions to emerging disturbances, such us reducing bottlenecks, and avoiding brake-downs and idleness of critical equipment in order to increase productivity and therefore, the company's competitiveness. The framework proposed in this research work includes machine monitoring techniques for the near real-time identification of machine status, in order to allow a predictive maintenance engine to diminish machine tool failures. Moreover, an adaptive short-term scheduling mechanism is employed, using monitoring data for the refinement of production schedules based on the current and future conditions of the shop-floor. Data acquired from a multisensory pilot installation together with information directly retrieved from the machine tool's controller are fused and comprise the input to subsequent software modules. The monitoring module is described, which analyses sensory data during the machine operation, as well as the Adaptive Scheduling Engine that dispatches schedules and refines future schedules based on awareness regarding machine availability. The software architecture and hardware setups are described and comprise the roadmap for the framework development. A possible application of the framework is described in the context of a European SME manufacturer.

Different Perspectives of a Factory of the Future: An Overview

“…From a virtual factory as an IT platform perspective, the potential is extended to plan, simulate, control the shop floor to assess the future impact of production and maintenance planning decisions [26]. Similarly, in a cloud environment, cloud-based services monitor the production planning and control the discrete manufacturing environment (i.e., machine availability monitoring and collaborative and adaptive process planning [21], simultaneous shop scheduling, and material planning [20]).…”

A cloud-based, knowledge-enriched framework for increasing machining efficiency based on machine tool monitoring

“…The application of monitoring devices in the shop-floor for tracking the availability of machine tools, results in an adaptive holistic scheduling has been introduced by [13,14]. The framework is introduced in five layers i.e.…”

Challenges and future perspectives for the life cycle of manufacturing networks in the mass customisation era

“…networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction'' [113]. Several applications have been reported in recent years where a cloud infrastructure is used to host and expose services related to manufacturing, such as: machine availability monitoring [114], collaborative and adaptive process planning [115], online tool-path programming based on real-time machine monitoring [116], manufacturing collaboration and data integration based on the STEP standard [117], and collaborative design [118].…”