Managing OEE to Optimize Factory Performance

"If you can not measure it, you can not improve it."(Lord Kelvin) It is a common opinion that productivity improvement is nowadays the biggest challenge for companies in order to remain competitive in a global market [1, 2]. A well-known way of measuring the effectiveness is the Overall Equipment Efficiency (OEE) index. It has been firstly developed by the Japan Institute for Plant Maintenance (JIPM) and it is widely used in many industries. Moreover it is the backbone of methodologies for quality improvement as TQM and Lean Production. The strength of the OEE index is in making losses more transparent and in highlighting areas of improvement. OEE is often seen as a catalyst for change and it is easy to understand as a lot of articles and discussion have been generated about this topic over the last years. The aim of this chapter is to answer to general questions as what to measure? how to measure? and how to use the measurements? in order to optimize the factory performance. The goal is to show as OEE is a good base for optimizing the factory performance. Moreover OEE’s evolutions are the perfect response even in advanced frameworks. This chapter begins with an explanation of the difference between efficiency, effectiveness and productivity as well as with a formal definition for the components of effectiveness. Mathematical formulas for calculating OEE are provided too. After the introduction to the fundamental of OEE, some interesting issues concerning the way to implement the index are investigated. Starting with the question that in calculating OEE you have to take into consideration machines as operating in a linked and complex environment. So we analyze almost a model for the OEE calculation that lets a wider approach to the performance of the whole factory. The second issue concerns with monitoring the factory performance through OEE. It implies that information for decision-making have to be guaranteed real-time. It is possible only through automated systems for calculating OEE and through the capability to collect a large amount of data. So we propose an examination of the main automated OEE systems from the simplest to high-level systems integrated into ERP software. Even data collection strategies are screened for rigorous measurement of OEE. The last issue deals with how OEE has evolved into tools like TEEP, PEE, OFE, OPE and OAE in order to fit with different requirements. At the end of the chapter, industrial examples of OEE application are presented and the results are discussed

An approach to evaluate the impact of the introduction of a disassembly line in traditional manufacturing systems

Purpose: The circular economy (CE) paradigm, traditionally based on the 3R (reuse, recycle, and remanufacture) principles, provides benefits for sustainability and represents a big opportunity for manufacturing enterprises to reduce costs and take economic advantages. This paper proposes an approach that can help stakeholders transition towards CE oriented business by evaluating the economic convenience of introducing a manual disassembly line to recover the components of End-of-Life (EoL) products in a traditional manufacturing system. Design/methodology/approach: The conceptual approach is generic and based on the characteristics of EoL products and on the reusability and recyclability features of every component. Then, based on the type of product and the disassembly sequence, the disassembly line is built in the virtual environment along the assembly line. The virtual environment must take into account the probabilistic parameters that characterise each real industrial context. Therefore, the assembly-disassembly lines are linked with the variables and economic functions needed to process the outputs of the approach application. Findings: Implemented in a virtual environment, the proposed approach evaluates a priori possible economic and environmental benefits coming from the integration of a disassembly line within a manufacturing context. The approach considers the variability of the EoL products’ status (their reusability and recyclability indices), provides the optimal number of operators that must be assigned to the manual disassembly line and determines the maximum reduction of the product cost that can be gained by introducing the disassembly line. Furthermore, an application example is provided to show the potential of the tool. Originality/value: Recently, the scientific literature has dealt with the issue related to the disassembly process of EoL products from several perspectives (e.g. disassembly line scheduling, planning, balancing, with and without the consideration of the quality of EoL products). However, to the best of our knowledge, no study provided an approach to evaluate the convenience of the investment in a disassembly line. Therefore, this document contributes to this research field by proposing a simple approach that supports the decision-making process of traditional manufacturing enterprises to evaluate a priori the economic return (i.e. how much the product cost decreases) and provide an estimate of the environmental benefits of integrating a manual disassembly line of EoL products with a traditional manufacturing systemPeer Reviewe

A model for the economic assessment of disassembly-line integration in traditional manufacturing processes

Abstract Managing End-of-Life (EoL) products and reintroducing materials and components within the production loop become crucial for guaranteeing the Circular Economy business model. In such a way, the proper management of disassembly process for recovering components and materials from returned EoL products is essential as well as strategic: disassembly is the main gateway of information and can ensure economic returns. This paper aims to provide a model for the economic assessment of the introduction of a manual disassembly line in a traditional and already operating assembly line of manufacturing industries. Therefore, recovered components and materials could directly feed the assembly lines and the recycling processes. The model takes in input probabilistic factors, as products' characteristics, and provides the operating times and component recovery indicators, as well as allows the sizing of the right number of operators needed in the new disassembly line through the optimisation of the industrial cost. An interesting natural evolution of this study is the development of a model-based simulator, with the aim of providing a user-friendly tool to industrial practitioners to estimate the economic feasibility and convenience of introducing a disassembly line

Special Issue: Smart manufacturing forsustainability: Trends and research challenges

Peer Reviewe

An Overview of Human Reliability Analysis Techniques in Manufacturing Operations

In recent years, there has been a decrease in accidents due to technical failures through technological developments of redundancy and protection, which have made systems more reliable. However, it is not possible to talk about system reliability without addressing the failure rate of all its components; among these components, "man" – because his rate of error changes the rate of failure of components with which he interacts. It is clear that the contribution of the human factor in the dynamics of accidents – both statistically and in terms of severity of consequences – is high [2]. Although valid values are difficult to obtain, estimates agree that errors committed by man are responsible for 60–90% of the accidents; the remainder of accidents are attributable to technical deficiencies [2,3,4]. The incidents are, of course, the most obvious human errors in industrial systems, but minor faults can seriously reduce the operations performances, in terms of productivity and efficiency. In fact, human error has a direct impact on productivity because errors affect the rates of rejection of the product, thereby increasing the cost of production and possibly reduce subsequent sales. Therefore, there is need to assess human reliability to reduce the likely causes of errors [1]. The starting point of this work was to study the framework of today’s methods of human reliability analysis (HRA): those quantitative of the first generation (as THERP and HCR), those qualitative of second (as CREAM and SPAR-H), and new dynamic HRA methods and recent improvements of individual phases of HRA approaches. These methods have, in fact, the purpose of assessing the likelihood of human error – in industrial systems, for a given operation, in a certain interval of time and in a particular context – on the basis of models that describe, in a more or less simplistic way, the complex mechanism that lies behind the single human action that is potentially subject to error [1]. The concern in safety and reliability analyses is whether an operator is likely to make an incorrect action and which type of action is most likely [5]. The goals defined by Swain and Guttmann (1983) in discussing the THERP approach, one of the first HRA methods developed, are still valid: The objective of a human reliability analysis is ‘to evaluate the operator’s contribution to system reliability’ and, more precisely, ‘to predict human error rates and to evaluate the degradation to human–machine systems likely to be caused by human errors in association with equipment functioning, operational procedures and practices, and other system and human characteristics which influence the system behavior’ [7]. The different HRA methods analysed allowed us to identify guidelines for determining the likelihood of human error and the assessment of contextual factors. The first step is to identify a probability of human error for the operation to be performed, while the second consists of the evaluation through appropriate multipliers, the impact of environmental, and the behavioural factors of this probability [1]. The most important objective of the work will be to provide a simulation module for the evaluation of human reliability that must be able to be used in a dual manner [1]: In the preventive phase, as an analysis of the possible situation that may occur and as evaluation of the percentage of pieces discarded by the effect of human error; In post-production, to understand what are the factors that influence human performance so they can reduce errors. The tool will also provide for the possibility of determining the optimal configuration of breaks through use of a methodology that, with assessments of an economic nature, allow identification of conditions that, in turn, is required for the suspension of work for psychophysical recovery of the operator and then for the restoration of acceptable values of reliability [1]

Modelling Hospital Materials Management Processes

Materials management is an important issue for healthcare systems because it influences clinical and financial outcomes. Before selecting, adapting and implementing leading or optimized practices, a good understanding of processes and activities has to be developed. In real applications, the information flows and business strategies involved are different from hospital to hospital, depending on context, culture and available resources; it is therefore difficult to find a comprehensive and exhaustive description of processes, even more so a clear formalization of them. The objective of this paper is twofold. First, it proposes an integrated and detailed analysis and description model for hospital materials management data and tasks, which is able to tackle information from patient requirements to usage, from replenishment requests to supplying and handling activities. The model takes account of medical risk reduction, traceability and streamlined processes perspectives. Second, the paper translates this information into a business process model and mathematical formalization. The study provides a useful guide to the various relevant technology-related, management and business issues, laying the foundations of an efficient reengineering of the supply chain to reduce healthcare costs and improve the quality of care

A Multi-parameter Model for Effective Configuration of Supply Chains

In this paper, a mathematical model for the strategic planning and design of supply chains in the globalization context is proposed. A multi-objective function is used to address decisions about capacity sizing, sourcing, and facility location, with the scope of maximizing supply chain profits. The model is dynamic and is applied to a multi- echelon, multi-facility and multi-product supply chain in hypotheses of delocalization. The model is characterized by the specific attention given to cost, revenue and financial factor modelling, which has been obtained by means of an activity-based approach and the inclusion of two drivers that are usually neglected in the literature: energy and labour. The model’s applicability and flexibility have been proved via a scenario analysis in which 12 different scenarios were implemented to reproduce the behaviour of major industries

The Role of Maintenance Operator in Industrial Manufacturing Systems: Research Topics and Trends

Maintenance contributes to gaining high business performance, guarantees system availability and reliability as well as safe and sustainable operations. Maintenance activity effectiveness depends on competences and the skills of operators whose performance strongly affects maintenance and production operations. The research field of human issues in industrial maintenance was deeply addressed in the literature; however, the current industrial paradigm, which focusses on the integration of new technologies in conventional manufacturing operations to support human performance, sheds light on new challenges for enterprises and opportunities for research in this field. While some literature reviews in the field of human errors and human factors are available, no study investigated the main topics, research trends and challenges related to the role of maintenance operators in manufacturing systems. This paper addresses the current state-of-the-art role of maintenance operators in manufacturing systems, providing an overview of the main studies. A systematic literature review was carried out to identify significant papers. Then, a topic modelling algorithm was used to detect the main topics of the selected papers to provide the research trends of the subject. The identified topics provided interesting research insights on the human role in industrial maintenance. Research trends and further research opportunities were defined

A survey study on Industry 4.0 readiness level of Italian small and medium enterprises

Abstract The Industry 4.0 (I4.0) paradigm is considered one of the most trending topics in the academic and industrial context, that involves emerging technologies that can make the processes increasingly integrated and provide digital solutions for supporting companies towards the greater flexibility required by the market. To date, the scientific literature strongly addressed the development of enabling technologies and the assessment of their impacts in different industrial contexts. However, there is a lack of studies providing empirical evidence about how manufacturing companies are facing the digital transformation, in particular for smaller industrial realities. For this reason, this paper aims to study the knowledge, readiness, and dissemination level of the I4.0 paradigm and enabling technologies for Italian Micro, Small, and Medium Enterprises (MSMEs). A web-based survey was conducted, and 77 companies were interviewed. The survey results underline that MSMEs still have limited knowledge about I4.0 and are not well prepared for its implementation