1,721,047 research outputs found
The quality chain: a total quality approach to external and internal supply chain management
No full textThe quality chain: a total quality approach to external and internal supply chain management
No full textThe quality chain: a total quality approach to external and internal supply chain management
No full textEnergy budget control in manufacturing systems with on-site energy generation: an advanced methodology for analyzing specific cost variations
Full text linkIn light of the growing competitiveness in global economy and the raising energy prices, energy budget management is an increasingly critical aspect for manufacturing companies. However, the analysis of the energy budget variation over time can be challenging due to numerous parameters affecting specific energy cost and energy consumption. The present study falls within the context of various works in literature concerning energy budget control and has the purpose of focusing the analysis on complex manufacturing systems including an on-site energy generation plant. In this case, the contributions of energy produced on-site, purchased and sold will contribute to the definition of the specific energy cost, which will be in turn influenced by several factors such as market prices of the resources (electricity, fossil fuel), specific characteristics of consumption (quantity and load synchronization), efficiency of the production system. In order to implement a comprehensive control of the energy budget, the difference between the predicted values and the real ones (budget variations) should be broken down into various components. This work proposes a methodology to decompose budget variations, defining a series of indicators at different levels associated to the single components influencing the variation itself, thus enabling the identification of the specific causes. This methodology has been developed in response to the demand of a specific company but can also be applied to others with similar configurations, given the interest recently aroused in this topic. Its application in an industrial context is then presented. The result of this work is the definition of a system of indicators allowing the identification of the different causes of the budget variance. The clear attribution of such deviations to different responsibility centers is enabled by the identification of a set of parameters to keep under control, hence supporting the company in the definition of timely countermeasures
Allocazione ottimale delle risorse finanziarie e configurazione impiantistica nella redazione di piani d’ambito (parte I)
No full textEvaluation of machine learning techniques to enact energy consumption control of compressed air generation in production plants
Full text linkIndustrial energy management is an important topic of discussion nowadays for both economic and sustainability reasons. A monitoring and control system able to guarantee the practice of a real-time control is a key point in enacting an effective management of energy consumption in a complex organization. In this context, the ISO 50000 family of standards suggest the application of different types of energy performance indicators (EnPIs), in a range of varying complexity: from simple absolute values of energy consumption, to statistical models, to engineering models. The evolution of machine learning techniques falls between the statistical and the engineering models, depending on the volume of data and the human involvement required for building a model. Therefore, the value of the present work is to explore the use of these tools, already consolidated in other fields, but not yet adequately assessed for energy performance control. In particular, the generation and distribution of compressed air is among the biggest uses of energy in production plants. This work starts with the application of the classical statistical approach and then proceeds to compare two different machine learning techniques, artificial neural networks and support vector machines, for the creation of energy performance indicators. The analysis begins comparing the feasibility of application, implementation complexity, data and level of human interaction required, making use of the results of a real application to a compressed air generation unit in a production plant. The comparison was then carried out using various performance indicators (R-squared, Mean Squared Error, Mean Absolute Percentage Error) as well as a graphical inspection of the resulting control charts produced with the different models. The work demonstrates the applicability of machine learning techniques in this specific context, proving them as an efficient compromise between the complexity and accuracy of statistical and engineering models
A joint application of design for six sigma and taguchi-response surface method in supply chain process design
Full text linkIn the current competitive context, the effective design of the supply chain process is even more important for businesses. Practitioners need to design robust and efficient processes that are at the same time focalized on business needs. In the present work we propose to combine two different methods: metamodel based design optimization (MBDO) and Design for Six Sigma (DFSS). The approach proposed, take advantage from DFSS structure to reduce the metamodel input variables. Most of MBDO techniques are complex and requires huge quantity of simulation. Therefore among the MBDO techniques, we have chosen to implement Taguchi and Response surface method (T-RSM). DFSS is a structured method, therefore easy to merge with other techniques and easily integrable with MBDO. In this paper we use T-RSM to obtain a robust metamodel performing a small number of simulations, therefore resulted less complex to apply than other MBDO techniques. The DFSS’s Method used in this paper was: DIDOV. The first two phases of DIDOV have been focalized on business goal and needs. In those phases degrees of freedom of the metamodel input variables were reduced. Merging DIDOV and T-RSM we got a reduced and focalized on business experiment plan. In this paper we show that the joint implementation of DFSS and T-RSM allows to obtain a design process focalized on business goal and leaner than other application of MBDO techniques in process design. A Case study of applying DFSS and MBDO is provided to show the implementation of this approach in a Supply chain process design. The presented approach results implementable in various context like product development and service process design
V. Cesarotti, G. Mummolo, L. Ranieri Allocazione ottimale delle risorse finanziarie e configurazione impiantistica nella redazione di piani d’ambito (parte II)
No full textA Framework for implementing lean through continuous improvement and Hoshin Kanri: a case study in Guanxi culture
No full textNowadays, the literature recognizes Lean as an integrated system. Despite its widespread adoption, literature highlights a lack of standard and success cases in the implementation of Lean. Hoshin Kanri (HK the literature) is recognized as a component for implementing new management systems and can play an essential role in Lean deployment. Cultural challenges are recurring issues in the literature. Organizational culture and workers’ cultural context could affect how HK and Lean are performed. This paper aim to provide a framework for Lean Deployment based on the principles of Hoshin Kanri, which allows the implementation of Lean through Continuous Improvement mechanisms. The innovation consists in incorporating the activities of the organizational culture setting in a Lean Deployment framework. The paper presents the implementation of a framework in the Chinese site of an international company. The case study highlights the importance of understanding organizational implications about lean implementation and possible resistance given by the Guanxi environment
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