Nowadays, Lean Manufacturing, Industry 4.0, and Sustainability are important concerns for the companies and in a general way for the society, principally, the influence of the two production philosophies, Lean Manufacturing and Industry 4.0, in the three main pillars of sustainability: economic, environmental, and social. According to the literature review done in this work, these relations are not well known and are dispersed by different sustainability’s criteria. To address this gap, this research proposes a structural equation model, with six hypotheses, to quantitatively measure the effects of Lean Manufacturing and Industry 4.0, in Sustainability. To statistically validate such hypotheses, we collected 252 valid questionnaires from industrial companies of Iberian Peninsula (Portugal and Spain). Results show that: (1) it is not conclusive that Lean Manufacturing is correlated with any of the sustainability pillars; and (2) Industry 4.0 shows a strong correlation with the three sustainability pillars. These results can contribute as an important decision support for the industrial companies and its stakeholders, even because not all the results are in line with other opinions and studies.

Each time a relevant proposal occurs, existing perspectives, concepts or fundamentals are confronted by emergent ones. The Industry 4.0 and its promoted production control systems based on Cyber-Physical Systems (CPS), made splash new potentials for the binomial human and technology (equipments and its settings). Several authors explore the envisaged required more physical and digital connection to announce interesting transformative changes, where self-configure and adaptive machines sustain the application of corrective decisions. This paper exposes a spectrum of existing CPS definitions and models and contributes with the fundamentals for an effective intelligent CPS (I-CPS), where a double loop learning process, allows its supporting software algorithms to be changed or reprogrammed. Instead, not only self-configure machines but its configuring software, too.

In order to set the stage for this special issue, the prime concepts are defined: i.e. “chaos,” “complexity,” “learning” (individual and organizational), “learning organization,” and “chaordic enterprise”. Also, several chaos‐and‐complexity‐related definitions of learning and learning organizations are provided. Next, the guest editors' main thesis is presented, namely that the “chaordic enterprise” might be the goal state towards which a company – seen as a learning organization – might evolve, and that the framework of “chaordic systems thinking” could be used as a meta‐model to inform a learning organization which is capable of self‐organization and transformative change under hyper‐turbulent conditions. Finally, in order to illustrate the contours of a chaordic enterprise, the case of a dynamically reconfigurable, globally integrated, networked enterprise is presented.

Integrated process planning and scheduling in networked manufacturing systems plays a crucial role nowadays and in the forthcoming context of Industry 4.0 to enable effective and efficient decisions, and to improve the business market, based on collaboration, along with computer-based distributed manufacturing and management functions. In this paper some insights regarding a literature review carried out about this main subjects analysed are presented and discussed. Moreover, a framework for integrated process planning and scheduling in networked manufacturing systems is proposed and briefly described, along with some main underlying issues, which are further discussed. Thus, the main purpose of this research consists on presenting a proposed methodology, based on the study conducted, to enable to further assist either academia or industry to develop new tools, techniques and approaches for integrated process planning in networked manufacturing environments. The findings and contributions of this research can help in the implementation and improvement in distributed manufacturing environments, to be linked with small and medium enterprises, to further expand their potentialities through well suited integrated process planning and scheduling decision making processes.