The implementation of the Industry 4.0 concept enables the flexibility, modularity and self-optimization of the manufacturing process. Process planning, placed in the value chain between construction and physical manufacturing, therefore, also demands digital transformation, while management of the transformation towards the new digital framework represents one of the most demanding challenges. Continuing the research on its structure and role within the smart factory, the main motivation for this work was to recognize the potential of the digital transformation of process planning elements, and to define the key dimensions that are essential for the readiness factor calculation and later transformational strategy formation, but also to recognize the current level of awareness of the Industry 4.0 concept among the process planners, along with the current use of its elements and key priorities for the transformation. The research has therefore been conducted in 34 Croatian metal machining companies, within which the influence of company size, level of education and familiarity with Industry 4.0 on final results and the stage of development have been investigated. The results have shown that the company size has a significant influence on the development stage and the use of certain elements wherein small and medium enterprises (SMEs) have already implemented certain digital elements, while they also tend to have a better fundamental infrastructure when using complex process planning methods, unlike others, which are still highly traditional. Organization and human resources have been ranked with the highest priority for change, while target goals for hardware and software have been set, with the managerial challenges of transformation defined and discussed.

Three-dimensional modelling software tools enable the creation of a digital replica of the product—“Digital Twin”—a representative of “Virtual Reality” as one of the prominent trends of Industry 4.0. The development of the Digital Twin can start simultaneously with the development of the product, primarily for the purpose of selecting optimal technical and technological solutions prior to and during physical construction, and, ultimately, with the intention of managing the entire product life cycle. The Digital Twin, as one of the key technological achievements in the implementation of the business system transformation from traditional to smart, should also be recognized as the cornerstone of the “Shipyard 4.0” model, i.e., its “Cyber-Physical Space.” This paper is based on statistical and empirical data of the observed shipyard with the aim to represent the significance of the Digital Twin ship in preserving and improving the competitiveness of the shipbuilding industry. Namely, with the emphasis this article places on the contribution of “advanced outfitting” in achieving savings in the shipbuilding process as well as its role in attaining high standards of environmental protection and workplace safety, the importance of its further improvement is an obvious conclusion—with Digital Twin being one of the recognized tools for this purpose.

Market positioning, i.e., the competitiveness of European shipyards, depends a lot on the measures of continuously improving the business processes, therefore meeting the criteria of environmental protection and sustainable energy. Lean management enables ongoing improvements of all system processes by recognizing and removing the unnecessary costs of the same, i.e., those activities which do not contribute to the added value for the customer. In this paper, the authors research the magnitude of improvements in the shipbuilding sales process achieved by applying the Lean tool “Value Stream Mapping” (VSM). The example of analysing the informational stream of the studied European shipyard’s existing sales process, performed by implementing the VSM, has defined the measures to decrease the losses in the process, with an emphasis on waiting time in internal and external communication. Upon VSM of the future state, measuring improvements realised by applying key performance indicators began. Significant cost savings in the sales process and the simultaneous increase of productivity of the employees participating in those process activities have been noted, as well as the substantial growth in sales and the shipyard’s income.

Today’s businesses face a critical need to balance sustainability, environmental responsibility, and operational excellence. Integrating lean and green methodologies holds promise for achieving this balance but presents challenges in real-sector implementation. Despite extensive research in the scientific community, a universally accepted model for integrated lean and green implementation is lacking. Limited research also explores the impact of lean tools on environmental performance indicators. This study aims to identify key economic and environmental performance indicators and investigate how they are influenced by lean tools. The primary objective is to develop a decision-making model facilitating lean tool implementation based on a company’s priorities for economic and environmental performance. The methodology involves a literature review, complemented by questionnaires and interviews with experts from academia and the real sector. The findings show that commonly used lean tools positively influence economic and environmental indicators. The decision-making model, tailored to chosen criteria priorities, was successfully validated using simulated and real company data, which makes it a potentially valuable resource for companies navigating integrated lean and green methodologies. While the obtained results show promise, it is important to highlight the limitations arising from the regional focus on Croatia and the inclusion of a subset of the manufacturing industry.

Today, companies need to continuously improve their production processes, which is a complex task. Lean manufacturing is one of the methodologies for production improvement, and one of the basic goals of any lean implementation is to reduce work-in-process (WIP) and shorten the production lead time. One of the basic lean principles for achieving these goals is pull principle. The adoption of this principle is quite challenging, as it requires a long-term commitment in the application and adoption of various lean techniques and tools that are prerequisites for the successful introduction of the pull principle. Kanban is the most well-known pull production control mechanism, and the first one developed within Toyota production system, but later, other pull control mechanisms were developed. Some of them include Conwip, Hybrid Kanban/Conwip, and Drum Buffer Rope (DBR), and those three, together with Kanban, were the research topic of this study. These four mechanisms were not explored and compared all together not for these specific production configurations considered in this research but also with regard to optimal parameters of control mechanisms. The goal was to analyze and compare how these pull control mechanisms affect lead time in different production conditions. For this purpose, simulation experiments were performed. The results showed that for different production conditions, different pull control mechanisms are optimal in terms of shortening lead time. This finding could help companies as a guideline for making a decision in terms of which pull control mechanism to choose.

The goal of any lean implementation in production process is achieving better production performances and one of them is productivity. Among many lean principles, pull principle is the most complex to achieve. There are different production control mechanisms for achieving pull and making decision which one to apply can be demanding because sometimes it is not obvious which is the best for specific situation. Many different production parameters influence production process and for one production setting, one control mechanism is the best choice, but for another production setting it might not be. One goal of this study was to research the influence of bottleneck in the production process in regard to achieving better productivity by applying pull principle. Some of the literature considered deals with the topic of bottleneck and pull but focuses only on bottleneck or in addition on one another production parameter and most of the literature studies up to three different pull control mechanisms. One of the objectives of this study was also to fill the research gap in a way to investigate more mechanisms, particularly, according to the literature, those most widely used in various production conditions with emphasis on bottleneck. The advantage of this research is that in addition to the bottleneck, other parameters, namely the number of control cards, variations and processing time are considered. For that reason, simulation experimentation was conducted and as a result regression functions modelling the relationship between productivity and mentioned parameters for four different pull control mechanisms are gained. The analysis showed that the existence of a bottleneck affects the effectiveness of pull mechanisms in terms of productivity.