Purpose The purpose of this paper is to gain insight into whether additive manufacturing (AM) represents incremental, radical, disruptive innovation or an industrial revolution and its implications. Design/methodology/approach This study applies a desk research strategy. Data were collected through a variety of industry sources as well as academic publications. Findings It was found that AM represents different innovations in different settings, while it represents incremental innovation in one industry, it has led to radical changes in other industries. There are also indications that it has a disruptive nature and some of the developments appear to be of the industrial revolutionary type, i.e. they cause fundamental shifts in society. Some explanation for the observed differences can come from different performance objectives. Research limitations/implications The spread of AM has been limited due to initial intellectual property protection. That means that while illustrations and examples were found for the different types of innovations, the level in which AM will ultimately penetrate manufacturing industries and society overall is not (yet) known. This calls for continued research for instance to study, in-depth, the adoption characteristics of AM in very specific settings. Practical implications Manufacturing is undergoing many changes as a consequence of the AM innovation. Many manufacturing industries have already been impacted through incremental changes as well as radical changes to entire industry dynamics. Manufacturers are advised to carefully monitor the continuous innovations in the technological capabilities of AM and their competitive and strategic consequences for adoption decisions. Social implications AM has an impact on many aspects of society because it affects many industries and enables household manufacturing. It has also affected education, i.e. the current generation of students in terms of skill requirements, and leads to legal difficulties in terms of intellectual property. Originality/value This study contributes to the understanding of the AM innovation and the widespread implications for different manufacturing industries and society at large.

Purpose The purpose of this paper is to explore what underlies the development of the consumer 3D printing industry and gain insight into future developments and its potentially disruptive impact on the existing manufacturing industry. Design/methodology/approach A combination of approaches was followed. Initially a consumer 3D printer was purchased to gain first-hand experience as part of a practical research case study. Results were discussed with manufacturers and additional information was sought, and triangulated, via a survey and an exploratory bibliometric study. Findings Many characteristics are in place to identify consumer 3D printing as a potential disruptive technology for the manufacturing industry. For example, the cost of consumer 3D printing is lower than for traditional manufacturing. However, the current adoption rate is low and the user friendliness and technological capabilities need to improve. Research limitations/implications The main limitation is the exploratory nature of the study which does not allow generalizations. Practical implications If developments and adoption patterns continue, then traditional manufacturing industries, distribution channels and the transportation sector may become threatened. Social implications Technological advances in consumer manufacturing can potentially threaten several economic sectors, which can lead to loss of jobs and affect budgets of states of countries that depend on sales tax. Originality/value One of the first studies to employ experiments in combination with other methods to gain insight into adoption patterns and the disruptive nature of consumer 3D printers specifically, rather than industrial 3D printers or new business models as a result of 3D printing technology.

In complex sociotechnical systems, cognitive and social humans use technology to make sense of situations when making decisions. These elements make sociotechnical systems difficult to develop. A modelling and assessment methodology for systems engineering is required to understand the sociotechnical system's behaviour and underlying structure. Modelling captures the dynamic interaction, as well as the effect of humans in a complex environment. Cognitive Work Analysis and System Dynamics are two complementary approaches applied in mutual support within this context. The objective of this paper is to demonstrate a modelling methodology for complex sociotechnical systems, in order to support the systems engineering process. OPSOMMINGIn komplekse sosio-tegniese stelsels, gebruik kognitiewe en sosiale mense tegnologie om situasies te verstaan en besluite te neem. Hierdie elemente maak sosio-tegniese stelsels moeilik om te ontwikkel. 'n Modellering en assessering metodologie vir stelselingenieurswese is nodig om die gedrag van die sosio-tegniese stelsel en onderliggende struktuur te verstaan. Modellering implementeer die dinamiese interaksie sowel as die effek van die mens in 'n komplekse omgewing. Kognitiewe werkanalise en Stelseldinamika is twee aanvullende benaderings wat binne hierdie konteks toegepas is in wedersydse ondersteuning. Hierdie artikel demonstreer 'n modellering metodologie vir komplekse sosiotegniese stelsels om die stelselsingenieurswese proses te ondersteun. INTRODUCTIONThe development of complex sociotechnical systems (STS) often consists of integrating new technology into existing systems through the application of systems engineering (SE) processes. Standard SE processes can struggle with complex STS, which exhibit dynamic behaviour as many unintended or unpredicted consequences may be experienced. The new artefact often leads to new task possibilities that evolve user requirements [1]. To overcome these difficulties, SE can apply modelling to explore structural, functional, and operational elements of the problem and solution space [2].STS theory, as developed by Trist [3], provides a framework for modelling and analysing complex systems. STS consists of humans applying technology to perform work through a process within a social structure (organisation) to achieve a defined objective [4,5]. Work can become complex due to dynamic interaction between the people themselves, between people and technology, and between people and the environment.The central aim of this paper is to demonstrate a modelling methodology for complex STS in support of the SE process. First, some background will be provided on the development of the modelling methodology before the model is demonstrated.

a b s t r a c tThis paper suggests that a system dynamics approach is best suited to assess the sustainability of technologies, with a specific emphasis on policy interventions for renewable energy in the African context. A bioenergy technology sustainability assessment (BIOTSA) model is subsequently demonstrated by analysing the outcomes of a proposed biodiesel production development on selected sustainability indicators for the Eastern Cape Province of South Africa. In addition, some scenarios are tested to compare how they may improve the selected indicators. The BIOTSA model results are useful to compare dynamic consequences that may result from the proposed biodiesel production development and the respective policies and decisions that may arise from such a development. Nevertheless, recommendations are made to improve the usefulness and practicability of this type of model for technology assessment purposes.

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The role that project risk management plays in ensuring the successful delivery of engineering and construction projects in South Africa is addressed in this paper. A survey questionnaire was developed to establish approaches used for risk management, and tools and techniques for risk identification. The findings revealed that project risk management had a significant role to play in the success of projects in South Africa. Respondents whose organisations practised structured risk management processes reported success in their projects. The main challenge was found to be in the implementation of risk management tools and techniques. Thus it became apparent that widespread adoption of project risk management in South Africa seemed to be impeded by a low knowledge and skills base, especially in terms of its application.

Project controls have been defined in the existing literature as managerial decisions and actions aimed at rectifying poor project performance. Understanding the potential unintended negative effects of such controls will be beneficial to project management practice and to the resulting project performance. Using the system dynamics approach, this article investigates some unintended negative effects of client project cost controls. Empirical data from a raw-water infrastructure project are used to calibrate the formulated system dynamics simulation model. Simulation results suggest that the client project cost controls (aimed at minimising project cost), unintentionally generate some counteractive effects (an increase in the project cost and the time schedule duration). OPSOMMING Projekkontroles is in die literatuur gedefinieer as bestuursbesluite en aksies wat daarop gemik is om swak projekprestasie reg te stel. Om die potensiële onbedoelde negatiewe gevolge van sulke kontroles te begryp, sal voordelig wees vir projekbestuurspraktyke en die gevolglike projekprestasie. Met behulp van ʼn stelseldinamika-benadering, ondersoek hierdie artikel 'n paar onbedoelde negatiewe gevolge van kliëntprojekkostekontroles. Empiriese data uit 'n rou-water-infrastruktuurprojek word gebruik om die geformuleerde stelseldinamika simulasiemodel te kalibreer. Simulasie resultate dui daarop dat die kliënt projek koste kontrole (gemik op die vermindering van projek koste), onbedoeld sommige teenproduktiewe effekte genereer ('n toename in die projek koste en die projek tydsduur).