A universal enterprise manufacturing services maturity model: a case study in a Chinese company

Li, Hao; Ji, Yangjian; Gu, Xinjian; Bao, Zhigang; Guo, Qi

doi:10.1080/0951192x.2013.814164

Cited by 15 publications

(10 citation statements)

References 23 publications

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“…Jin et al (2014), similarly, define a set of NSD success factors and group them into dimensions, namely: strategy management, process formalization, knowledge management and customer involvement. The four-stage product-centric service MM by Li et al (2014) considers four dimensions: sales profit source, service business composition, service process quality and service infrastructure. Neff et al (2014) developed a MM for the heavy equipment manufacturing industry to assess the information systems support to the product service system (PSS).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Servitization often requires developing new activities or redesigning the current ones. Marketing and sales activities, fleet maintenance planning, product retrofit, revamping, disposal and reverse logistic processes (Barquet et al , 2013; Liu et al , 2014) may be (re-)designed. Moreover, companies need the capability to communicate and make tangible the value for the customer of new offerings (Kindström and Kowalkowski, 2009; Reim et al , 2015).…”

Section: The Servitization Maturity Model (Semm)mentioning

confidence: 99%

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A maturity model for the servitization of product-centric companies

Adrodegari

Saccani

2020

JMTM

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PurposeThe purpose of this paper is to contribute to the understanding of the servitization phenomenon of product-centric companies, by identifying the resources, capabilities and organizational aspects needed to successfully deploy a servitized business model (BM).Design/methodology/approachBy adopting a literature-based approach, this paper develops a servitization maturity model (SeMM) aimed at assessing and positioning companies in the servitization journey. The paper also illustrates the model application to two small and medium-sized enterprises (SMEs), a machinery and a forklift truck company.FindingsThe SeMM identifies a set of 85 critical requirements that are used to evaluate the servitization level of product-centric companies, through a specific five-stage measurement scale. The requirements are categorized into: five maturity dimensions (organizational approach, process management, performance management, tools, capabilities) and nine BM Canvas components. The empirical application exemplifies how the SeMM can support managers in identifying and bridging the gaps in their servitization journey.Originality/valueThe SeMM adopts an original bi-dimensional approach and provides an operationalization of the servitization process through the identification of specific critical requirements framed on established BM and maturity dimensions taken from the literature. Moreover, the model responds to a call for research to develop practitioner-oriented tools and guidelines to support the servitization process, in particular for SMEs, and to the need to go beyond to measures of servitization based on indicators about number of services offered or their turnover.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: The Servitization Maturity Model (Semm)mentioning

confidence: 99%

A maturity model for the servitization of product-centric companies

Adrodegari

Saccani

2020

JMTM

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“…The universal enterprise manufacturing service maturity model is provided to evaluate and level the service development phase which can help in scientific decision-making (Li et al 2014). Definitions, classifications and measurement methods are presented to evaluate the composition's flexibility so that the optimal-selection based on flexibility can be enabled (Guo et al 2012).…”

Section: Related Workmentioning

confidence: 99%

“…Hence manufacturing enterprises can focus on their own core functionality and collaborate with each other to gain more agile, flexible and efficient manufacturing operations (Zupančič, Sluga, and Butala 2012) without impacting their core compatibility (Badr, Peng, and Biennier 2012). Modern manufacturing services have played an increasingly significant role for the development of the manufacturing enterprises (Li et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Domain-aware reputable service recommendation in heterogeneous manufacturing service ecosystem

Fan

Huang

Tan

et al. 2014

International Journal of Computer Integrated Manufacturing

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Networked manufacturing becomes an important manufacturing method for modern manufacturing enterprises. With the wide adoption of service-oriented architecture and cloud manufacturing, manufacturing enterprises and organisations publish their manufacturing capability, such as resources, processes and knowledge as manufacturing services. A rapidly growing manufacturing service ecosystem can be observed nowadays, which brings the information overload problem for the service selection. Thus, how to organise these services and how to recommend the reputable services become two important issues for the manufacturing service retrieval and reuse. In this paper, the service cluster method WSTPCluster, which develops the topic model based on Latent Dirichlet Allocation, is employed to cluster services into specific domains. As the service ecosystem can be modelled as a heterogeneous service network, a unified reputation propagation method URPM is proposed to calculate the reputation of services and to distinguish the reputable services in each domain. Combining WSTPCluster and URPM, domain-aware reputable service recommendation method is introduced to recommend the high reputable services in each domain for the consumers. Experiments show that this method brings a better performance both in the recommendation accuracy and in the long tail recommendation.

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“…Manufacturing system based on IOT, information sensing technology as the driving force, to promote the development of manufacturing industry, to the direction of globalization and informatization. With the continuous emergence of new manufacturing mode, networked manufacturing [2]- [5], cloud manufacturing [6]- [8], service oriented manufacturing [9]- [11] provide the theoretical and technical support to improve the overall operation and management level of the manufacturing industry.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of monitoring and Management System for Discrete Manufacturing Process Based on IOT Technology

Lu¹,

Sheng²

2015

Proceedings of the 2nd International Conference on Civil, Materials and Environmental Sciences

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Abstract-For active perception of multi-source information, coupling of heterogeneous information, and effective integration of manufacturing information and knowledge layer, this paper proposed some key technologies and a new implementation framework. The RFID and other sensing technologies were used to acquire the multi-source heterogeneous information. It developed a monitoring and management system for discrete manufacturing process, based on the Internet of Things. The main function modules of the system were characterized. It has been realized active sensing and dynamic optimization of manufacturing process information, and put forward a new mode and way for quantitative analysis and tracking decision optimization of multi-source heterogeneous information. IOT, as the key theory and technology of information technology industry, has been effectively applied in many fields, such as logistics [12] and industrial automation [13]. Nevertheless, there are some exceptions in real-time monitoring of production process. In recent years, the research of some typical discrete manufacturing enterprises shows that, in the process of implementation, the demand and challenges of traditional MES concentrate on such aspects: Keywords(1) The real-time and accuracy of multi-source heterogeneous information collection With the expanding industrial production and personalized market demand, information are massive and multi-source heterogeneous in discrete manufacturing process. Lack of effectively real-time automatic acquisition and active perception, multi-source heterogeneous information cannot be obtained timely, and integration of data and knowledge layer is not good in manufacturing information system [14][15].(2) The relevance and effectiveness of perceptual informationThe physical space and information space is strongly associated, non deterministic and highly mixed [16]. It brings a great challenge to the discrete manufacturing monitoring common modeling, unified description and system design. It urgent needs a comprehensive analysis and description for the coupling and correlation mechanism of information space and physical space [17].(3) The real-time dynamic management of manufacturing process information and resourcesThe production model has changed from mass to "just in time" (JIT) , materials tracking and production monitoring are required more timely, flexible and complicated. Due to a lack of production planning and timely feedback of manufacturing process information, it is difficult to conduct effective control and scheduling to the manufacturing process, and real-time monitoring and dynamic optimization of production resources, tasks and quality.In view of the present situation of backward multi-source heterogeneous information collection method and poor in real time of data, integrating IOT technology, it proposed an open, hierarchical and scalable network framework of monitoring and management system for discrete manufacturing process. The application of IOT technology in discrete manufacturing process, ...

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A universal enterprise manufacturing services maturity model: a case study in a Chinese company

Cited by 15 publications

References 23 publications

A maturity model for the servitization of product-centric companies

A maturity model for the servitization of product-centric companies

Domain-aware reputable service recommendation in heterogeneous manufacturing service ecosystem

Design and Implementation of monitoring and Management System for Discrete Manufacturing Process Based on IOT Technology

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