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The purpose of this paper is to propose a new business process representation adapted to the needs of Industry 4.0 to facilitate the implementation of technological solutions in the construction sector.

This work is based on the Design Research Methodology approach and includes four phases: (1) a literature review on the main business process modeling standards and their ability to take into account the specificities of Industry 4.0; (2) the identification of the attributes to be considered to model Industry 4.0 processes; (3) the development of a mapping model for Industry 4.0; and (4) the validation of the model using a case study from the construction sector.

To the authors’ knowledge, current business process modeling standards do not effectively represent business processes in the context of Industry 4.0.

The proposed model can represent not only the 4.0 solutions that can be implemented in the construction sector, particularly from a technology and data perspective but also measures, with the help of performance indicators, the impacts of successive process changes in terms of skills, cost and time for a true 4.0 transformation.

Enterprises often face a wide variety of adverse events. Adverse events can have negative effects on organizations like failures of resources. In case resources fail, they are not available and cannot perform the assigned work. Enterprises are therefore especially interested in how resilient processes and workflows are in case adverse events occur and resources may fail. For this purpose, process resilience measurement approaches are needed.

To measure the resilience of processes and workflows, a life cycle and five quantitative metrics have been developed. The metrics have been validated using five real-world production and logistics cases to show their applicability on process models and paths. Furthermore, workshops have been conducted with professionals to get additional feedback on the contributions.

Based on the results obtained from applying the metrics to five real-world cases, view-based resilience improvements can be derived. Overall, only one of the five real-world cases can be considered as completely resilient. Furthermore, the metrics and life cycle have been especially valued by professionals with respect to transparency, independency, comparability as well as the ability to determine critical process paths.

Several authors have dealt with different aspects related to the measurement of business processes, resilience or a combination thereof. However, a life cycle or metrics to quantitatively measure the resilience of processes by considering resources has not been found yet. The life cycle and metrics are therefore novel. As a future research direction, they can be applied in different domains for further validation purposes.

In this paper, the gamma test is used to determine the order of lag-k tail dependence existing in financial time series. Using standardized return series, statistical evidences based on the test results show that jumps in returns are not transient. New time series models which combine a specific class of max-stable processes, Markov processes, and GARCH processes are proposed and used to model tail dependencies within asset returns. Estimators for parameters in the models are developed and proved to be consistent and asymptotically joint normal. These new models are tested on simulation examples and some real data, the S&P 500.

The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.

This study aims to develop a modular and prescriptive digital transformation maturity model whose constituent elements have conceptual integrity as well as reveal the priority weights of maturity model components.

A literature review with a concept-centric analysis enlightens the characteristics of constituent parts and reveals the gaps for each component. Therefore, the interdependency network among model dimensions and priority weights are identified using decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP) method, including 19 industrial experts, and the results are robustly validated with three different analyses. Finally, the applicability of the developed maturity model and the constituent elements are validated in the context of the manufacturing industry with two case applications through a strict protocol.

Results obtained from DEMATEL-based ANP suggest that smart processes with a priority weight of 17.91% are the most important subdimension for reaching higher digital maturity. Customer integration and value, with a priority weight of 17.30%, is the second most important subdimension and talented employee, with 16.24%, is the third most important subdimension.

The developed maturity model enables companies to make factual assessments with specially designed measurement instrument including incrementally evolved questions, prioritize action fields and investment strategies according to maturity index calculations and adapt to the dynamic change in the environment with spiral maturity level identification.

A novel spiral maturity level identification is proposed with conceptual consistency for evolutionary progress to adapt to dynamic change. A measurement instrument that is incrementally structured with 234 statements and a measurement method that is based on the priority weights and leads to calculating the maturity index are designed to assess digital maturity, create an improvement roadmap to reach higher maturity levels and prioritize actions and investments without any external support and assistance.

The purpose of this paper is to present a business process measurement framework for the evaluation of a corpus of business processes modelled in different business process modelling approaches. The results of the application of the proposed measurement framework will serve as a basis for choosing business process modelling approaches.

The approach uses ideas of the goal question metric framework to define metrics for measuring a business process where the metrics answer the questions to achieve the goal. The weighted sum method (WSM) is used to aggregate the measure of attributes of a business process to derive an aggregate measure, and business process modelling approaches are compared based on the evaluation of business process models created in different business process modelling approaches using the aggregate measure.

The proposed measurement framework was applied to a corpus of business process models in different business process modelling approaches and is showed that insight is gained into the effect of business process modelling approach on the maintainability of a business process model. From the results, business process modelling approaches which imbibed the principle of separation of concerns of models, make use of reference or base model for a family of business process variants and promote the reuse of model elements performed highest when their models are evaluated with the proposed measurement framework. The results showed that the applications of the proposed framework proved to be useful for the selection of business process modelling approaches.

The novelty of this work is in the application of WSM to integrate metric of business process models and the evaluation of a corpus of business process models created in different business process modelling approaches using the aggregate measure.

The traditional methods for process modeling emphasize the process workflow considerations at the cost of the associated process structure and resource communication. In the real process world, however, all these aspects are integrated and appear simultaneously: the workflows are driven by communication across the structure of resources. The aim of this paper is to explore a new approach based on an innovative, two‐dimensional view of the process world in an enterprise, integrating the workflow, the structure, and the communication from the beginning on.

Contrary to the traditional methods, the workflow diagrams are not directly designed by the process modeler, but rather they are automatically generated from the connectivity of specified resource communication. The modular documentation contains text and graphic information about the entire process world (structure of process resources, structure of process workflows, resource communication and interaction, communication through internal/external interfaces).

A new systematic approach to modular, process‐oriented enterprise description has been developed. Its two‐dimensional model allows an integrated visualization of the entire process world. The resulting process documentation is absolutely consistent and of very high quality. The user‐friendly access to information is made possible by clear interdependencies of process‐defining objects embedded in a relational documentation model. An update of the complete documentation can be performed automatically from the common database. The successful software implementation of the prototype application and its use in small customer projects demonstrate the practical feasibility of the two‐dimensional approach.

The two‐dimensional process modeling (2DPM) is a new systematic approach to modular process‐oriented enterprise description. A software implementation based on the underlying model together with professional programming tools and principles would be necessary to arrive at a marketable product.

The purpose of this paper is to identify the relationships between process modeling and Industry 4.0, the strategic themes and the most used process modeling language in smart factories. The study also presents the growth of the field of study worldwide, the perspectives, main challenges, trends and suggestions for future works.

To do this, a science mapping was performed using the software SciMAT, supported by VOS viewer.

The results show that the Business Process Model and Notation (BPMN), Unified Modelling Language (UML) and Petri Net are the most relevant languages to smart manufacturing. The authors also highlighted the need to develop new languages or extensions capable of representing the dynamism, interoperability and multiple technologies of smart factories.

It was possible to identify the most used process modeling languages in smart environments and understand how these languages assist control and manage smart processes. Besides, the authors highlighted challenges, new perspectives and the need for future works in the field.

A Process Model During the last five years, American businesses have increasingly accepted the notion that product quality is necessary for them to compete in today′s world markets. Product quality, in the context here, can be defined by an agreed set of standards and tolerance limits between the firm and its customers. Quality is achieved through the successful creation of form, possession, time, place, and quantity utilities for the firm′s products. Control must be implemented in order to ensure that these utilities are created to meet the standards and tolerance limits agreed upon by the firm and its customers. The purpose of exercising control is to ensure that desired results are attained from an activity or process. As such, it is important to exercise control over the logistics activities to make sure that time, place, and quantity utilities are created in accordance with customer needs. The purpose of this monograph is to present a rather comprehensive discussion of the concept of control. Specific control concepts presented include a discussion of the link between control and quality, the development of the characteristics of control and levels of sophistication of control, the presentation of an eclectic process control model, and suggestions to managers on how to implement the control process over logistics activities.

Although software systems used to automate business processes have been becoming rather advanced, the existing practice of developing and modifying graphical process models in those software systems is still primitive: users have to manually add, change, or delete each node and arc piece by piece. Since such manual operations are typically tedious, time‐consuming, and prone to errors, it is desirable to develop an alternative approach. This paper aims to address this issue.

In this paper, a novel, human‐understandable process manipulation language (PML) for specifying operations (e.g. insertion, deletion, merging, and split) on process models is developed. A prototype system to demonstrate PML is also developed.

The paper finds that manipulation operations on process models can be standardized and, thus, can be facilitated and automated through using a structured language like PML.

PML can improve manipulation operations on process models over the existing manual approach in two aspects: first, using PML, users only need to specify what operations are to be performed on process models, and then a computer carries out specified operations as well as performs other routine operations (e.g. generating nodes and arcs). This feature minimizes user effort to deal with low‐level details on nodes and arcs. Second, using PML, users can systematically specify operations on process models, thus reducing arbitrary operations and problems in process models.