Performance measurement and management. A literature review focussed on the role played by management theories with a deep dive into the industry 4.0 environment

PURPOSE: The aim of this paper is to review the theoretical lenses used in performance measurement and management in a traditional and industry 4.0 environment and to contribute to understanding the current state of research in the field and its future development. DESIGN/METHODOLOGY/APPROACH: This paper performs a structured review of the existing performance measurement and management literature, with the objective to investigate the current state of research, looking at popular theories in more detail, as well as to propose possible avenues for future consideration for the field to develop further moving forward. Particularly, this paper focusses on and identifies (1) theoretical lenses that are dominating this field, (2) the role played by specific theories and the way different theories are used together and finally, (3) an in-depth dive into relevant theories for performance measurement and management applied in an industry 4.0 environment. FINDINGS: Key findings highlight the growing number of publications, leading authors and journals where research is published. The findings also include the identification and detailed analysis of the most popular theories leveraged by scholars also in reference to research methodologies. A thorough analysis of Industry 4.0 performance measurement and management is then carried out, as this is one of the identified emerging themes in the research field. Findings here include the identification of relevant research and the suggestion of significant theories that can help build this specific body of knowledge. ORIGINALITY/VALUE: This research offers a key contribution by providing a powerful “theoretical toolkit” to researchers and practitioners working in performance measurement and management and industry 4.0 fields

Quality management in the industry 4.0 era

In the current competitive scenario, manufacturing companies are facing various challenges related to an increasing level of variability. This variability means different sets of dimensions such as demand, volume, process, technology, quality, customer behavior and supplier attitude, and transform the industrial systems engineering domain. A new paradigm tries to solve these challenges and solutions such as "the fourth industrial revolution" or "Industry 4.0" refers to new production patterns, including new technologies, productive factors and labor organizations, which are completely changing the production processes and developing high-efficiency production systems that make it possible to minimize production costs and improve production and product quality. Manufacturing companies need to achieve a substantial improvement in performance by manufacturing high-quality products and creating highly flexible systems that make it possible to maintain their efficiency even when demand varies dramatically. Tools for the management and optimization of quality are vitally important. In this way the adoption of highly flexible cyber physical production units permits the implementation of production processes capable of guaranteeing high-quality standards in the finished product, even in the case of small production lots. Industry 4.0 provides promising opportunities for quality management therefore, the purpose of this paper is to focus on the quality management and industry 4.0 concepts and analyze the current state of literature trying to understand the implications and opportunities for quality management in the industry 4.0 era

Digitalization technologies for industrial sustainability

Digital technologies are shown to perform a potential role in developing a resource efficient industrial base. The effective adoption of them can help to deliver reduced costs and improve the flexibility and sustainability of manufacturing systems. However, these positive benefits are far from guaranteed and the way in which digital technologies favor the transition towards sustainable manufacturing systems has not been analyzed in detail yet, so more conceptual and empirical investigations are required in this field. This paper develops a conceptual framework, which explains the potential significance of using digital technologies toward efficiency, resilience and sustainability. It also includes evidence from various case studies, which illustrate the core technologies which can potentiality contribute to a sustainable industrial future. The findings show some impressive results concerning the sustainable implications of the digitalization of manufacturing processes. If the predicted benefits can be achieved through digital technologies, they could massively impact on sustainability. \ua9 2019 The Authors. Published by Elsevier B.V

Cyber-physical systems (CPS) in supply chain management: From foundations to practical implementation

Since 2015 developments such as Industry 4.0 and cyber-physical production systems on the technology side, and approaches such as flexible and smart manufacturing systems hold great potential. These in turn give rise to special requirements that the production planning, control and monitoring, among others, needing a paradigm shift to exploit the full potential of these methods and techniques. Starting from foundations in Cyber Physical Systems (CPS), building upon definitions and findings reported by literature, a practical example of innovative Cyber Physical Supply Chain Planning System (CPS2) is provided. The paper clarifies the advantages of cyber-physical systems in the production planning, controlling and monitoring perspective with respect to manufacturing, logistics and related planning practices. A set of basic features of CPS2 systems are discussed and addressed by contextualizing service orientation architecture and microservices components with respect to supply chain management collaboration and cooperation practices. The identification of specific technologies behind those functions, within the developed research, provides some practical insight if the interesting CPS2 potential

A Review of Production Planning Models: Emerging features and limitations compared to practical implementation

In the last few decades, thanks to the interest of industry and academia, production planning (PP) models have shown significant growth. Several structured literature reviews highlighted the evolution of PP and guided the work of scholars providing in-depth reviews of optimization models. Building on these works, the contribution of this paper is an update and detailed analysis of PP optimization models. The present review allows to analyze the development of PP models by considering: i) problem type, ii) modeling approach, iii) development tools, iv) industry-specific solutions. Specifically, to this last point, a proposed industrial solution is compared to emerging features and limitations, which shows a practical evolution of such a system

A Novel Methodology for Manufacturing Firms Value Modeling and Mapping to Improve Operational Performance in the Industry 4.0 Era

Abstract In recent years there has been appreciable academic activity in manufacturing value creation resulting in that the ability to create value is based on the competence to make decisions and implement strategies; even though this evidence it is still difficult to understand where the company's weak points are located so value modeling approaching is arising. In this study Authors first report a qualitative review on value creation and modeling based on the identification, selection and analysis of about 100 papers, then specify the value concept within manufacturing companies. Within this context the Authors describe a novel methodology for manufacturing value modeling from strategic level down to operational improvements. The methodology and the related mapping and analysis tools have been co-developed with Siemens MES division within Industry 4.0 context. The Manufacturing Value Modeling Methodology (MVMM) is based on 5 steps: Value Map, Maturity Model, Gap and Process Analysis, Validation and Improvement Areas Definition. Through this methodological approach, a series of structured interviews allowing to construct the value map accordingly to the current company maturity model and the relationships between the strategic objectives and operational practices, capabilities, and methods. Combining the assessments interview with the Company' resources, infrastructure and IT structures, it is possible to establish a current level of the company. The mapping step is followed by a gap and process analysis, assessing most relevant areas for the creation of value aiming at constructing an interventions roadmap, setting out priorities and activities to be improved. The selection of the improvement areas defines process initiatives, KPIs and interventions to improve business alignment. To provide a practical view of the methodology a sample of the Value Modeler tool is presented and discussed

Towards building a standard dataset for Arabic keyphrase extraction evaluation

Keyphrases are short phrases that best represent a document content. They can be useful in a variety of applications, including document summarization and retrieval models. In this paper, we introduce the first dataset of keyphrases for an Arabic document collection, obtained by means of crowdsourcing. We experimentally evaluate different crowdsourced answer aggregation strategies and validate their performances against expert annotations to evaluate the quality of our dataset. We report about our experimental results, the dataset features

Generation of Antibunched Light by Excited Molecules in a Microcavity Trap

The active microcavity is adopted as an efficient source of non-classical light. By this device, excited by a mode-locked laser at a rate of 100 MHz, single-photons are generated over a single field mode with a nonclassical sub-poissonian distribution. The process of adiabatic recycling within a multi-step Franck-Condon molecular optical-pumping mechanism, characterized in our case by a quantum efficiency very close to one, implies a pump self-regularization process leading to a striking n-squeezing effect. By a replication of the basic single-atom excitation process a beam of quantum photon (Fock states) can be created. The new process represents a significant advance in the modern fields of basic quantum-mechanical investigation, quantum communication and quantum cryptography