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1 – 10 of 13Marcello Braglia, Davide Castellano, Marco Frosolini, Mosè Gallo and Leonardo Marrazzini
The paper proposes a new workforce effectiveness metric that is a sophisticated evolution of a pre-existing overall labour effectiveness (OLE) indicator. The KPI, named revised…
Abstract
Purpose
The paper proposes a new workforce effectiveness metric that is a sophisticated evolution of a pre-existing overall labour effectiveness (OLE) indicator. The KPI, named revised OLE (ROLE), provides a structured methodology to measure in a holistic way the losses relating to labour, maintaining some formal similitude to the overall equipment effectiveness (OEE)
Design/methodology/approach
A new structure of losses is proposed to overcome the drawbacks and the difficulties that usually affect the data collection stage, referring to directly measurable quantities or, when this is not the case, suggesting a viable method to quantify the loss. Besides, this approach facilitates the comprehension of labour-related issues, suggesting potential countermeasures. The novel ROLE indicator has been defined, based on this new structure, to evaluate the labour effectiveness in batch process industries. A real case study is provided, which explains the methodology and illustrates the capability of the corresponding KPI.
Findings
The present work analyses the labour performance indexes available in literature, with the aim of evidencing those aspects that can be properly observed and quantified and, at the same time, categorizing them to identify their possible drawbacks. A new structure of losses is derived, with respect to four different categories, which may help to measure the losses themselves more effectively
Originality/value
The paper investigates some important KPIs dealing with labour performance and individuates some significant drawbacks. Then it suggests a new, inclusive structure of losses and a modified KPI that not only measures effectiveness but also allows to identify viable countermeasures.
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Marcello Braglia, Francesco Di Paco, Marco Frosolini and Leonardo Marrazzini
This paper presents Quick Changeover Design (QCD), which is a structured methodological approach for Original Equipment Manufacturers to drive and support the design of machines…
Abstract
Purpose
This paper presents Quick Changeover Design (QCD), which is a structured methodological approach for Original Equipment Manufacturers to drive and support the design of machines in terms of rapid changeover capability.
Design/methodology/approach
To improve the performance in terms of set up time, QCD addresses machine design from a single-minute digit exchange of die (SMED). Although conceived to aid the design of completely new machines, QCD can be adapted to support for simple design upgrades on pre-existing machines. The QCD is structured in three consecutive steps, each supported by specific tools and analysis forms to facilitate and better structure the designers' activities.
Findings
QCD helps equipment manufacturers to understand the current and future needs of the manufacturers' customers to: (1) anticipate the requirements for new and different set-up process; (2) prioritize the possible technical solutions; (3) build machines and equipment that are easy and fast to set-up under variable contexts. When applied to a production system consisting of machines subject to frequent or time-consuming set-up processes, QCD enhances both responsiveness to external market demands and internal control of factory operations.
Originality/value
The QCD approach is a support system for the development of completely new machines and is also particularly effective in upgrading existing ones. QCD's practical application is demonstrated using a case study concerning a vertical spindle machine.
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Marcello Braglia, Gionata Carmignani, Marco Frosolini and Andrea Grassi
To provide a structured methodology to permit an optimal selection of the best suited Computer Managed Maintenance System (CMMS) software within process industries.
Abstract
Purpose
To provide a structured methodology to permit an optimal selection of the best suited Computer Managed Maintenance System (CMMS) software within process industries.
Design/methodology/approach
The analysis has been executed adopting a multi‐attribute decision making methodology, namely the analytic hierarchic process (AHP) technique. A specific hierarchic structure has been defined considering 46 criteria outlined via questionnaires and interviews with administration, production and maintenance managers of several industries. To improve the effectiveness of the methodology, AHP has been coupled with a sound sensitivity analysis.
Findings
The application of the proposed approach allows the maintenance practitioners to concentrate on a limited subset of CMMS applications and to compare their actual capabilities in order to select the right one, rather than considering only their purchase cost.
Practical implications
The methodology enables decision makers to restrict the selection process to a limited number of software programmes that better suit the actual requirements of the corporation's personnel and to help the managers involved in the choice to better understand what each software can offer to them to effectively help the management of maintenance‐related activities. Finally, the choice is driven by objective considerations rather than by subjective opinions, and the purchase and the following implementation of the CMMS can be better justified to the corporation top‐level management
Originality/value
The paper proposes a robust approach, structured and useful in practice, for the selection of a CMMS software, that takes into account multiple, often conflicting, criteria and overcomes the intrinsic limitations of subjective decisions
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Maurizio Bevilacqua, Marcello Braglia, Marco Frosolini and Roberto Montanari
To suggest that a multi layer perception based artificial neural network (MLP‐ANN) is a practical instrument to evaluate the expected failure rates of 143 centrifugal pumps used…
Abstract
Purpose
To suggest that a multi layer perception based artificial neural network (MLP‐ANN) is a practical instrument to evaluate the expected failure rates of 143 centrifugal pumps used in an oil refinery plant.
Design/methodology/approach
A MLP is adopted to weigh up the correlation existing among the failure rates and the several different operating conditions which have some influence in the occurrence.
Findings
During the training phase, it is possible to discriminate among those variables closely significant for the final outcome and those which can be kept off from the analysis. In particular, the neural network automatically calculates and classifies the centrifugal pumps in terms of both the failure probability and its variability degree, giving a better analysis instrument to take decisions and to justify them, in order to optimise and fully support an eventual preventive maintenance (PM) program.
Originality/value
Aids in decision‐making to reduce the necessity of reactive maintenance activities and to simplify the planning of PM ones.
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Marcello Braglia, Marco Frosolini and Roberto Montanari
This paper presents a tool for reliability and failure mode analysis based on an advanced version of the popular failure mode, effects and criticality analysis (FMECA) procedure…
Abstract
This paper presents a tool for reliability and failure mode analysis based on an advanced version of the popular failure mode, effects and criticality analysis (FMECA) procedure. To help the analyst formulating efficiently effective criticality assessments of the possible causes of failure, the fuzzy logic technique is adopted. Particular attention has been devoted to support the maintenance staff with a fuzzy criticality assessment model easy to implement and design. To test the proposed methodology, an actual application concerning a process plant in milling field for human consumption flour is showed in the paper.
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Marcello Braglia, Davide Castellano and Marco Frosolini
The purpose of this paper is to present a reliability centered maintenance (RCM) embedded integer linear programming approach (suited to the budget monetary resources allocation…
Abstract
Purpose
The purpose of this paper is to present a reliability centered maintenance (RCM) embedded integer linear programming approach (suited to the budget monetary resources allocation task) to the maintenance strategies mix selection for an industrial plant equipment.
Design/methodology/approach
The developed approach allows to determine the optimal maintenance strategies mix for a set of equipment in a more quantitative way than the classic RCM approach. The proposed model takes into account, for each potential failure determined using the FMECA and for each admissible strategy, the costs and the potential risk priority number (RPN) reduction. Finally, an industrial case concerning an Italian paper-mill plant is reported to demonstrate the effectiveness of the approach presented.
Findings
The paper finds that the application of the proposed approach allows to optimally allocate the budget monetary resources, determining which suitable maintenance practice apply to each failure, taking into account the costs of each strategy and the potential reduction of the RPN.
Practical implications
The proposed model permits to assign (during the budget monetary resources allocation task) to each failure the optimal strategy, among a set of suitable maintenance practices, considering the costs and the estimated RPN reduction.
Originality/value
The paper proposes a completely new RCM embedded approach to the maintenance strategies selection, in order to optimally allocate the budget monetary resources. This model overcomes the limits of the traditional RCM approach, taking into account quantitative aspects, i.e. the compatibility constraint between failures and policies, the maintenance strategies costs, and the RPN estimated reduction.
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Marcello Braglia, Marco Frosolini and Francesco Zammori
Overall equipment effectiveness (OEE) is the key metric to measure the performance of individual equipment. However, when machines operate jointly in a manufacturing line, OEE…
Abstract
Purpose
Overall equipment effectiveness (OEE) is the key metric to measure the performance of individual equipment. However, when machines operate jointly in a manufacturing line, OEE alone is not sufficient to improve the performance of the system as a whole. The purpose of this paper is to show how to overcome this limitation, by presenting a new metric (overall equipment effectiveness of a manufacturing line – OEEML) and an integrated approach to assess the performance of a line.
Design/methodology/approach
An alternative losses classification structure is developed to divide the losses that can be directly ascribed to equipment, from the ones that are spread in the line. Starting from this losses classification structure, an approach based on OEE is developed to evaluate the criticalities and the effectiveness of the line.
Findings
This method has been applied to an automated line for engine basements production. Results show that OEEML successfully highlights the progressive degradation of the ideal cycle time, explaining it in terms of: bottleneck inefficiency, quality rate, and synchronisation‐transportation problems.
Research limitations/implications
OEEML alone fails to explain to which extent effectiveness is supported by in process‐inventories and should be integrated with additional metrics to estimate the inventories‐related costs.
Practical implications
OEEML provides practitioners with an operative tool useful to highlight the points where the major inefficiencies take place and to foresee the potential benefits of corrective actions.
Originality/value
In relation to other methodologies, OEEML presents two main advantages: it detects and quantifies the line's critical points and it can be applied even in presence of buffers, without underestimating the efficiency of the system.
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Massimo Bertolini, Maurizio Bevilacqua, Marcello Braglia and Marco Frosolini
In this paper an experience dealing with the analysis of maintenance outsourcing by means of multi‐criteria decision methods (MCDM) is reported. In particular, the analytic…
Abstract
In this paper an experience dealing with the analysis of maintenance outsourcing by means of multi‐criteria decision methods (MCDM) is reported. In particular, the analytic hierarchy process technique (AHP) is used as a managerial decision support system to select the best alternative between different outsourcing contracts in terms of maintenance services. The proposed methodology has been tested on an industrial case study dealing with an important italian brickwork. This application shows how the AHP is able to support the choice of the correct level of the maintenance activities outsourcing. In particular, the hierarchic decisional structure developed represents an instrument able to give a well balanced synthesis of several different factors that must be taken into account during this type of decision problem.
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Francesco Zammori, Marcello Braglia and Marco Frosolini
The purpose of this paper is to define the standard structure of a vendor managed inventory (VMI) agreement, which can be used as a guideline for the early definition of the…
Abstract
Purpose
The purpose of this paper is to define the standard structure of a vendor managed inventory (VMI) agreement, which can be used as a guideline for the early definition of the agreement.
Design/methodology/approach
Starting from an industrial application of relevance, the information flow and the technical details, which are to be defined before the operation startup, are identified and discussed. These data are used as the key points for the definition of the basic frame of the agreement. A particular emphasis is given to the “Technical Specification” and the “Service Level Agreement” sections.
Findings
It is shown that a VMI agreement should be arranged into parts dealing with the generic and legal sides of the agreement, whereas the technical aspects and the relation‐specific topics should be addressed in the annexes. This increases the flexibility of the agreement in that, as the VMI relationship evolves over time, changes will affect only the annexes leaving the main body of the agreement unaltered.
Practical implications
The proposed agreement has a flexible structure and can be easily adopted by the personnel involved to correctly define and implement VMI in several industrial fields.
Originality/value
By approaching VMI from a practical point of view, this paper identifies the main issues that must be covered in the agreement to fit the needs of both parties and to assure benefits on both sides.
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V. Raja Sreedharan and R. Raju
The purpose of this paper is to review Lean Six Sigma (LSS) literature and report different definitions, demographics, methodologies and industries.
Abstract
Purpose
The purpose of this paper is to review Lean Six Sigma (LSS) literature and report different definitions, demographics, methodologies and industries.
Design/methodology/approach
This paper highlights various definitions by different researchers and practitioners. A total of 235 research papers has been reviewed for the LSS theme, research methodology adopted, type of industry, author profile, country of research and year of publication.
Findings
From the review, four significant LSS classifications were identified that deal with the spread of LSS in different industries followed by observation for classification.
Practical implications
LSS is a strategy for success, but it did not examine its presence in various Industries. From this paper, readers can understand the quantum of its spread before implementing LSS. For academicians, it will be a comprehensive list of papers for research.
Originality/value
This paper reviews 235 research papers for their year, author profile, research methodology and type of industry. Various characteristics of LSS definitions and their theme are also reviewed.
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