Establishment of a maturity model to assess the development of industrial AI in smart manufacturing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wenting Chen ◽  
Caihua Liu ◽  
Fei Xing ◽  
Guochao Peng ◽  
Xi Yang

PurposeThe benefits of artificial intelligence (AI) related technologies for manufacturing firms are well recognized, however, there is a lack of industrial AI (I-AI) maturity models to enable companies to understand where they are and plan where they should go. The purpose of this study is to propose a comprehensive maturity model in order to help manufacturing firms assess their performance in the I-AI journey, shed lights on future improvement, and eventually realize their smart manufacturing visions.Design/methodology/approachThis study is based on (1) a systematic review of literature on assessing I-AI-related technologies to identify relevant measured indicators in the maturity model, and (2) semi-structured interviews with domain experts to determine maturity levels of the established model.FindingsThe I-AI maturity model developed in this study includes two main dimensions, namely “Industry” and “Artificial Intelligence”, together with 12 first-level indicators and 35 second-level indicators under these dimensions. The maturity levels are divided into five types: planning level, specification level, integration level, optimization level, and leading level.Originality/valueThe maturity model integrates indicators that can be used to assess AI-related technologies and extend the existing maturity models of smart manufacturing by adding specific technical and nontechnical capabilities of these technologies applied in the industrial context. The integration of the industry and artificial intelligence dimensions with the maturity levels shows a road map to improve the capability of applying AI-related technologies throughout the product lifecycle for achieving smart manufacturing.

2016 ◽  
Vol 116 (8) ◽  
pp. 1468-1492 ◽  
Author(s):  
Marco Comuzzi ◽  
Anit Patel

Purpose While it is commonly recognised that Big Data have an immense potential to generate value for business organisations, appropriating value from Big Data and, in particular, Big Data-enabled analytics is still an open issue for many organisations. The purpose of this paper is to develop a maturity model to support organisations in the realisation of the value created by Big Data. Design/methodology/approach The maturity model is developed following a qualitative approach based on literature analysis and semi-structured interviews with domain experts. The completeness and usefulness of the model is evaluated qualitatively by practitioners, whereas the applicability of the model is evaluated by Big Data maturity assessments in three real-world organisations. Findings The proposed maturity model is considered exhaustive by domain experts and has helped the three assessed organisations to develop a more critical understanding of the next steps to take. Originality/value The maturity model integrates existing industry-developed maturity models into one single coherent Big Data maturity model. The proposed model answers the call for research on Big Data to abstract from technical issues to focus on the business implications of Big Data initiatives.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanjai Kumar Shukla ◽  
Sushil

PurposeOrganizational capabilities are crucial to achieve the objectives. A plethora of maturity models is available to guide organizational capabilities that create a perplexing situation about what stuff to improve and what to leave. Therefore, a unified maturity model addressing a wide range of capabilities is a necessity. This paper establishes that a flexibility maturity model is an unified model containing the operational, strategic and human capabilities.Design/methodology/approachThis paper does a comparative analysis/benchmarking studies of different maturity models/frameworks widely used in the information technology (IT) sector with respect to the flexibility maturity model to establish its comprehensiveness and application in the organization to handle multiple goals.FindingsThis study confirms that the flexibility maturity model has the crucial elements of all the maturity models. If the organizations use the flexibility maturity model, they can avoid the burden of complying with multiple ones and become objective-driven rather than compliance-driven.Research limitations/implicationsThe maturity models used in information technology sectors are used. This work will inspire other maturity models to adopt flexibility phenomena.Practical implicationsThe comparative analysis will give confidence in application of flexibility framework. The business environment and strategic options across organizations are inherently different that the flexibility maturity model well handles.Social implicationsA choice is put to an organization to see the comparison tables produced in this paper and choose the right framework according to the prevailing business situation.Originality/valueThis is the first study that makes a conclusion based on comparative benchmarking of existing maturity models.


2021 ◽  
Vol 7 ◽  
pp. e661
Author(s):  
Raghad Baker Sadiq ◽  
Nurhizam Safie ◽  
Abdul Hadi Abd Rahman ◽  
Shidrokh Goudarzi

Organizations in various industries have widely developed the artificial intelligence (AI) maturity model as a systematic approach. This study aims to review state-of-the-art studies related to AI maturity models systematically. It allows a deeper understanding of the methodological issues relevant to maturity models, especially in terms of the objectives, methods employed to develop and validate the models, and the scope and characteristics of maturity model development. Our analysis reveals that most works concentrate on developing maturity models with or without their empirical validation. It shows that the most significant proportion of models were designed for specific domains and purposes. Maturity model development typically uses a bottom-up design approach, and most of the models have a descriptive characteristic. Besides that, maturity grid and continuous representation with five levels are currently trending in maturity model development. Six out of 13 studies (46%) on AI maturity pertain to assess the technology aspect, even in specific domains. It confirms that organizations still require an improvement in their AI capability and in strengthening AI maturity. This review provides an essential contribution to the evolution of organizations using AI to explain the concepts, approaches, and elements of maturity models.


2018 ◽  
Vol 33 (6) ◽  
pp. 792-803 ◽  
Author(s):  
Khadijeh Momeni ◽  
Miia Martinsuo

Purpose The purpose of this paper is to better understand the efficient use of remote monitoring systems (RMS) to create business value for industrial services in manufacturing firms. A business view to RMS is a key prerequisite for the successful application of the Internet of Things (IoT) in industrial services. Design/methodology/approach A qualitative multiple-case study was conducted in six engineering companies. The main source of data was semi-structured interviews with 16 managers. Findings The findings highlight the role of RMS in enabling manufacturing firms to collect data from customers to complement their limited knowledge about their customers. The study demonstrates the business value of using RMS in industrial services and the necessity of capturing the business value through advanced IT technologies. Research limitations/implications The qualitative research design and choice of six target companies limit the findings to business-to-business manufacturing firms. Further, the focus is on the manager’s viewpoint. The findings imply new business value through an efficient use of RMS to complement direct customer contact. Practical implications The study draws attention to the skilled use of advanced RMS and information and communication technology as a prerequisite for the successful application of the IoT in manufacturing firms that provide services for complex solutions and customers dispersed globally. Originality/value The research shows that using information collected through RMS is an important factor in creating business value in a manufacturing firm’s customer relationships. The study contributes by integrating RMS into the customer information collection process to increase the amount, validity and quality of data.


2018 ◽  
Vol 38 (3) ◽  
pp. 810-827 ◽  
Author(s):  
Sambit Lenka ◽  
Vinit Parida ◽  
David Rönnberg Sjödin ◽  
Joakim Wincent

Purpose The dominant-view within servitization literature presupposes a progressive transition from product to service orientation. In reality, however, many manufacturing firms maintain both product and service orientations throughout their servitization journey. Using the theoretical lens of organizational ambivalence, the purpose of this paper is to explore the triggers, manifestation and consequences of these conflicting orientations. Design/methodology/approach A multiple case study method was used to analyze five large manufacturing firms that were engaged in servitization. Semi-structured interviews were conducted with 35 respondents across different functions within these firms. Findings Servitizing firms experience organizational ambivalence during servitization because of co-existing product and service orientations. This paper provides a framework that identifies the triggers of this ambivalence, its multi-level manifestation and its consequences. These provide implications for explaining why firms struggle to implement servitization strategies due to co-existing product and services orientations. Understanding organizational ambivalence, provides opportunity to manage related challenges and can be vital to successful servitization. Originality/value Considering the theoretical concept of ambivalence could advance the understanding of the effects and implications of conflicting orientations during servitization in manufacturing firms.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Matthew Mark Tyson ◽  
Nicholas J. Sauers

PurposeThe purpose of this study is to examine school leaders' experiences with adoption and implementation of artificial intelligence systems in their schools. It examined the factors that led educational administrators to adopt one artificial intelligence program (ALEKS) and their perceptions around the implementation process.Design/methodology/approachThis was a qualitative case study that included structured interviews with seven individuals who have adopted artificial intelligence programs in their schools. Participants were identified through purposive and snowball sampling. Interview transcripts were analyzed and put through a two-step coding process involving in vivo coding as well as pattern coding.FindingsTwo major themes emerged from this study pertaining to the state of the diffusion of artificial intelligence through the adoption and implementation process. The findings indicated that school leaders were actively engaged in conversations related to AI adoption and implementation. They also created structures (organizational) to ensure the successful adoption and implementation of artificial intelligence.Originality/valueThis is an original study that examined the experiences of school leaders who have adopted and implemented artificial intelligence in their schools. The body of literature related to artificial intelligence and school leadership is extremely limited.


Author(s):  
Ehap Sabri ◽  
Rohan Vishwasrao

The authors describe how organizations can leverage the maturity model approach in conjunction with foundational concepts of perspective-based performance evaluation models like the balanced scorecard (BSC) to define a comprehensive performance measurement framework. A maturity model by design provides a road-map to the next level of performance. In this chapter, the authors propose using maturity models as a structured way of identifying current capability or maturity level of any supply chain. The authors provide guidance on selecting the right “causal linkages” between supply chain objectives and performance measures. They then define a mechanism for specifying even more granular definitions of measures linked to strategic objectives, as the level of maturity progresses. In this chapter, the authors survey widely used supply chain/business process maturity models and current practices related to measuring operational metric. And then present a tiered framework for operational metric alignment and KPI governance based on perspective-based modeling design principles.


Author(s):  
Temitope Seun Omotayo ◽  
Prince Boateng ◽  
Oluyomi Osobajo ◽  
Adekunle Oke ◽  
Loveline Ifeoma Obi

Purpose The purpose of this paper is to present a capability maturity model (CMM) developed to implement continuous improvement in small and medium scale construction companies (SMSCC) in Nigeria. Design/methodology/approach A multi-strategy approach involving qualitative studies of SMSCC in Nigeria was conducted. Semi-structured interviews were conducted with purposively selected construction experts in Nigeria to identify variables essential for continuous improvement in SMSCC. Data collected were thematically analysed using NVIVO. Subsequently, a system thinking approach is employed to design and develop the CMM for implementing continuous improvement SMSCC, by exploring possible relationships between the variables established. Findings CMM provided a five-level approach for the inclusion of investigated variables such as team performance; culture; structure; post-project reviews, financial risk management, waste management policy and cost control. These variables are factors leading to continuous improvement in SMSCC, implementable within a six to seven and a half years’ timeline. Practical implications The system thinking model revealed cogent archetypes in the form of reinforcing loops that can be applied in developing the performance of SMSCC. Continuous improvement is feasible. However, it takes time to implement. Further longitudinal studies on the cost of implementing continuous improvement through CMM a knowledge transfer project can be initiated. Originality/value A methodical strategy for enhancing the effectiveness and operations of SMSCC in developing countries can be extracted from the causal loop diagram and the CMM.


2018 ◽  
Vol 11 (2) ◽  
pp. 187
Author(s):  
Jabier Retegi Albisua ◽  
Juan Ignacio Igartua López

Purpose: In order to achieve excellence, outsourced maintenance contractors in Oil&Gas sector play a key role due to the important impact of their task on security, availability and energy consumption. This paper presents the process followed in order to implement a Supplier Development Program in a refinery using Company Maturity Model (CoMM) and the results obtained in three cases validating the method to obtain a strategic improvement project medium term grid.Design/methodology/approach: The methodology followed consists of constructing a CoMM capturing the knowledge existing in the refinery and applying it with three supplier improvement teams. Findings and conclusions have arised through an observation of the three processes and extracting common conclusions.Findings: The resulting CoMM has been used for self-assessment by three suppliers and has demonstrated its potential to define a medium-term improvement project road map validated by the customer. Furthermore, during the design and application processes, the contribution of CoMMs to the SECI process of knowledge management has been observed.Practical implications: The use of CoMMs in a service contractor context can be applied in other sectors. It contributes to alignment of targets between the supplier and customer companies and to knowledge sharing inside both firms.Originality/value: Maturity models in many transversal fields (CMMI, EFQM, BPMM, PEMM, etc.) have been thoroughly studied in the literature. Less effort has been made analysing the case of using maturity models constructed and implemented by a company for its specific purposes. In this paper, the process followed by a company to establish a Supplier Development Process using CoMMs is described.


2019 ◽  
Vol 30 (7) ◽  
pp. 1005-1033
Author(s):  
Pooja Chaoji ◽  
Miia Martinsuo

Purpose This paper empirically investigates the processes by which manufacturing firms create radical innovations in their core production process, referred to as radical manufacturing technology innovations (RMTI). The purpose of this paper is to improve the understanding of the processes and practices manufacturing firms use to create RMTI. Design/methodology/approach Creation processes for 23 RMTI projects from diverse industry and technology contexts are explored. Data were collected via semi-structured interviews, and an inductive analysis was carried out to identify similarities and differences in RMTI types and creation processes. Findings Three types of RMTI and three alternative RMTI creation processes are revealed and characterized. An integrated view is developed of the activities of the equipment supplier and the manufacturing firm, highlighting their different roles and interaction across the three RMTI creation process types. Research limitations/implications The exploratory design limits the depth of the analysis per RMTI project, and the focus is on manufacturing technology innovations in one country. The results extend previous case and context-specific findings on RMTI creation processes and provide novel frameworks for cross-case comparisons. Practical implications The manufacturing firms’ proactive role in RMTI creation is defined. A framework is proposed for using different RMTI creation processes for different types of RMTI. Originality/value This study addresses recent calls for empirical research on understanding the ways in which process innovations unfold in manufacturing firms. The findings emphasize the role of manufacturing firms as creators of RMTI in addition to their role as innovation adopters and implementers and reveal the suitability of different RMTI creation processes for different RMTI types.


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