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Research Article

Workshop digitalisation and its effect on manufacturing operations management: a new analysis method from a data quality perspective

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Article: 2330076 | Received 18 Mar 2023, Accepted 10 Mar 2024, Published online: 29 Mar 2024
 

ABSTRACT

Workshop digitalisation (WD) provides a rich supply of real-time production data to achieve efficient manufacturing operations management (MOM). However, if data quality (DQ) cannot be ensured, manufacturing enterprises will not benefit from WD despite the resources invested. This study proposes a new method to evaluate the effect of WD from a data quality (DQ) perspective and identifies the root causes of WD failures at the operational level by information stream analysis based on an extended value stream mapping 4.0 (VSM4.0). The method is developed through a Design Science Research (DSR) approach and tested in an automobile parts manufacturer in China.

Nomenclature

This section provides the notations used in Section 4.2
=

Represents a relational database scheme

=

Represents a relational scheme

A=

Represents an attribute of a relational scheme

D=

Represents a domain of an attribute

I,I=

Represents an instance of a relational (database) scheme

t=

Represents a tuple in an instance

v,v=

Represents a (tuple of) constant(s) or variable(s)

x,x=

Represents a (tuple of) variable(s)

a,a=

Represents a value assignment to a (tuple of) variable(s)

P, Q=

Represents an atom

θ=

Represents a comparison operator

Agg(•)=

Represents an aggregation function

exp=

Represents an expression in an aggregation function

fc=

Represents a filtering condition in an aggregation function

c=

Represents a denial constraint

f(•), w(•)=

Represents a function

Acknowledgments

This work was supported by the Projects of the National Natural Science Foundation of China under Grant 72188101; and the Chinese Institute For Quality Research.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China.

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