Energy saving policies for a machine tool with warm-up, stochastic arrivals and buffer information

One of the measures for saving energy in manufacturing is the implementation of control strategies that reduces energy consumption during the machine idle periods. Specifically, the paper proposes a framework that integrates different control policies for switching the machine off when the production is not critical, and on either when the part flow has to be resumed or the queue has accumulated to a certain level. A general policy is formalized by modeling explicitly the power consumed in each machine state. A threshold policy is analyzed and the optimal parameter is provided for an M/M/1/K system. Numerical results are based on data acquired with dedicated experimental measurements on a real machining centre, and a comparison with common practices in manufacturing is also reported

Energy efficient control strategy for machine tools with stochastic arrivals and time dependent warm-up

Energy efficiency in manufacturing is becoming a challenging goal due to the demand of this sector in the worldwide scenario. One of the measures for saving energy is the implementation of control strategies that reduce machine energy consumption during the machine idle periods. This paper extends a threshold policy, that switches off the machine during interruptions of part flow, by modelling explicitly the warm-up time as dependent on the time period the machine stays in low power consumption state. The optimal policy parameter is provided numerically for general distributions of the part arrival time and general functions modelling the warm-up time. Numerical results are based on data acquired with dedicated experimental measurements on a real machining center

Energy Saving Opportunities and Value of Information: A Trade-off in a Production Line

A general framework for switching the machine off/on has been recently proposed in literature for single machines. However, the amount of information available along the production system is often limited and it might be not trivial to understand which information provides more benefits. This paper studies the performance of a production line when several control policies are applied at machine level. The amount of information at machine level varies and the trade-off with energy reduction is investigated. The considered performance measures are the energy consumed per part and the system throughput. Numerical results are based on discrete event simulation

A New Learning Factory Experience Exploiting LEGO For Teaching Manufacturing Systems Integration

Involving and stimulating students through intensive work in computer laboratories and simulation projects might be a challenging task, often due to the lack of the real manufacturing system that must be modeled and improved. Indeed, studying a manufacturing system that cannot be observed represents a real obstacle for student effective learning. In this paper, we describe the "LEGO FACTORY" initiative, an extra-curricular experience within the Master Degree Study Program in Mechanical Engineering of Politecnico di Milano. The initiative is open to students from any study course of the university. The goal is to exploit learning-by-playing principles to offer scholars the possibility to understand the most common issues in the design and management of manufacturing systems, with a focus on system integration. A miniaturized production system made with LEGO® MINDSTORMS® is provided to students who are asked to accomplish a project aiming at the improvement of the system performances. The participants work in teams and must introduce design modifications and develop technical solutions to address the requirements. The experience is described with the hope that the approach can be replicated in other environments

A Cardinality-constrained Approach for Robust Machine Loading Problems

The Machine Loading Problem (MLP) refers to the allocation of operative tasks and tools to machines for the production of parts. Since the uncertainty of processing times might affect the quality of the solution, this paper proposes a robust formulation of an MLP, based on the cardinality-constrained approach, to evaluate the optimal solution in the presence of a given number of fluctuations of the actual processing time with respect to the nominal one. The applicability of the model in the practice has been tested on a case study

Benchmarking the sustainable manufacturing paradigm via automatic analysis and clustering of scientific literature: A perspective from Italian technologists

The number of scientific papers in the field of Sustainable Manufacturing (SM) shows a strong growth of interest in this topic in the last 20 years. Despite this huge number of publications, a clear statement of the profound meaning of Sustainable Manufacturing, or at least a strong theoretical support, is still missing. The 6R framework seems to be a first attempt to rationalize this issue, as it is an axiomatic identification of its true nature. Recognizing the pursuing of one or more of the Reduce-Recycle-Reuse-Recover-Redesign-Remanufacture principles allows users to identify if any manufacturing action is in the right direction of sustainability. In the paper, the authors speculate on the use of this framework and its possible extension by referring to all the existing scientific contributions on Sustainable Manufacturing in the SCOPUS® databases as a source of data. Starting from the measurement of the distribution of the scientific papers allocated onto the 6Rs dimensions, by using both author keywords and automatically extracted multiword from texts, the distribution of the scientific papers among the 6R was derived. A new framework is proposed based on analytical text tools to compare the affinity of the applied research activities of the Italian Technologist network SOSTENERE to sustainable manufacturing, and provide also a benchmarking view to describe the Italian way to SM with respect to the rest of existing applications

Benchmarking the sustainable manufacturing paradigm via automatic analysis and clustering of scientific literature: A perspective from Italian technologists

The number of scientific papers in the field of Sustainable Manufacturing (SM) shows a strong growth of interest in this topic in the last 20 years. Despite this huge number of publications, a clear statement of the profound meaning of Sustainable Manufacturing, or at least a strong theoretical support, is still missing. The 6R framework seems to be a first attempt to rationalize this issue, as it is an axiomatic identification of its true nature. Recognizing the pursuing of one or more of the Reduce-Recycle-Reuse-Recover-Redesign-Remanufacture principles allows users to identify if any manufacturing action is in the right direction of sustainability. In the paper, the authors speculate on the use of this framework and its possible extension by referring to all the existing scientific contributions on Sustainable Manufacturing in the SCOPUS® databases as a source of data. Starting from the measurement of the distribution of the scientific papers allocated onto the 6Rs dimensions, by using both author keywords and automatically extracted multiword from texts, the distribution of the scientific papers among the 6R was derived. A new framework is proposed based on analytical text tools to compare the affinity of the applied research activities of the Italian Technologist network SOSTENERE to sustainable manufacturing, and provide also a benchmarking view to describe the Italian way to SM with respect to the rest of existing applications

Analysis on Energy Efficient Switching of Machine Tool With Stochastic Arrivals and Buffer Information

One of the measures for saving energy is the implementation of control strategies that reduce energy consumption during the machine idle periods. This paper proposes a framework that integrates different control policies for switching the machine off when the production is not critical, and on when the part flow has to be resumed. A general policy is formalized by modeling explicitly the power consumed in each system state. With this policy, the service can be resumed according to time threshold and when N parts have accumulated in the buffer. The behavior of the control strategy under different scenarios is numerically evaluated. Numerical results are based on data acquired with dedicated experimental measurements on a real machining center. A comparison with the common practice in manufacturing and with control policies that do not consider buffer information is also reported

Energy-efficient control strategies for machine tools with stochastic arrivals

Energy saving in production plants is becoming more and more relevant due to the pressure from governments to contain the environmental impact of manufacturing and from companies to reduce costs. One of the measures for saving energy is the implementation of control strategies that reduce energy consumption during the machine idle periods. This paper proposes a framework that integrates different control policies for switching the machine off when production is not critical and on when the part flow has to be resumed. A general policy is formalized by modelling explicitly the energy consumed at each machine state. The policy parameters that minimize the requested machine expected energy are provided analytically for general distributions. Numerical results are based on data acquired with dedicated experimental measurements on a real machining centre, and a comparison with the most common practices in manufacturing is also reported. Note to Practitioners-The paper analyzes the control problem of switching off-on a machine tool for energy saving during the idle times. Different control policies are investigated pointing out the most significant factors. A mapping of the optimal control policy as a function of warm-up time and mean part arrival time is also provided. An algorithm is described for identifying the optimal control parameters. The results of this research will be useful for a practical implementation of a switching policy for energy saving. This implementation requires the fitting of the distribution modelling the part arrival times, the estimation of the warm-up time, and the estimation of the power adsorbed by the machine in four different states

Analysis of an energy oriented switching control of production lines

The implementation of control strategies that reduce energy consumption during the machine idle periods is becoming a challenging goal to achieve energy efficiency in production systems. A general framework for switching the machine off! on has been recently proposed in literature for single machines. This paper studies the performance of a production line when a general policy is applied at machine level. The considered performance measures are the total energy consumed per part and the system throughput. Numerical results are based on discrete event simulation, and a comparison with the most common practices in manufacturing is also reported