Fused filament fabrication (FFF) is a cost-effective additive manufacturing method that makes use of thermoplastics to produce customised products. However, there are several limitations associated with FFF that are adversely affecting its growth including variety of materials, rough surface finish and poor mechanical properties. This has resulted in the development of metal-infused thermoplastics that can provide better properties. Furthermore, FFF-printed parts can be subjected to post-processes to improve their surface finish and mechanical properties. This work takes into consideration two commonly used polymeric materials, i.e., ABS (acrylonitrile butadiene styrene) and PLA (polylactic acid) and compares the results with two metal-infused thermoplastics i.e., copper-enhanced PLA and aluminium-enhanced ASA (acrylonitrile styrene acrylate). The four different materials were subjected to a post-process called annealing to enhance their mechanical properties. The effect of annealing on these four materials was investigated through dimensional analysis, ultrasonic testing, tensile testing, microstructural analysis and hardness testing. The results showed that annealing affects the materials differently. However, a correlation among ultrasonic testing, tensile testing and microstructural analysis was observed for all the materials based on their crystallinity. It was found that the semi-crystalline materials (i.e., PLA and copper enhanced PLA) showed a considerable increase in tensile strength post-annealing. However, the amorphous materials (ABS and aluminium-enhanced ASA) showed a comparatively lower increase in tensile strength, demonstrating that they were less receptive to annealing. These results were supported by higher transmission times and a high percentage of voids in the amorphous materials. The highest hardness values were observed for the ASA material and the lowest for the ABS material. This work provides a good comparison for the metal-infused thermoplastics and their applicability with the commonly used PLA and ABS materials.

Process reengineering (PR) in manufacturing organizations is a big challenge, as shown by the high rate of failure. This research investigated different approaches to process reengineering to identify limitations and propose a new strategy to increase the success rate. The proposed methodology integrates data as a procedure for process identification (PI) and mapping and incorporates process verification to analyze the changes made in a specific process. The study identifies interdependency within the manufacturing process (MP) and proposes a generic process reengineering approach that uses simulation and analysis of production line data as a method for understanding the changes required to optimize the process. The paper discusses the methodology implementation technique as well as process identification and the process mapping technique using simulation tools. It provides an improved data-driven process reengineering framework that incorporates process verification. Based on the proposed model, the study investigates a production line process using the WITNESS Horizon 21 simulation package and analyse the efficiency of data-driven process reengineering and process verification in terms of implementing changes.

Digital transformation is no longer a future trend, as it has become a necessity for businesses to grow and remain competitive in the market. The fourth industrial revolution, called Industry 4.0, is at the heart of this transformation, and is supporting organizations in achieving benefits that were unthinkable a few years ago. The impact of Industry 4.0 enabling technologies in the manufacturing sector is undeniable, and their correct use offers benefits such as improved productivity and asset performance, reduced inefficiencies, lower production and maintenance costs, while enhancing system agility and flexibility. However, organizations have found the move towards digital transformation extremely challenging for several reasons, including a lack of standardized implementation protocols, emphasis on the introduction of new technologies without assessing their role within the business, the compartmentalization of digital initiatives from the rest of the business, and the large-scale implementation of digitalization without a realistic view of return on investment. To instill confidence and reduce the anxiety surrounding Industry 4.0 implementation in the manufacturing sector, this paper presents a conceptual framework based on business process management (BPM). The framework is informed by a content-centric literature review of Industry 4.0 technologies, its design principles, and BPM method. This integrated framework incorporates the factors that are often overlooked during digital transformation and presents a structured methodology that can be employed by manufacturing organizations to facilitate their transition towards Industry 4.0.

Industry 4.0 (also referred to as digitization of manufacturing) is characterized by cyber physical systems, automation, and data exchange. It is no longer a future trend and is being employed worldwide by manufacturing organizations, to gain benefits of improved performance, reduced inefficiencies, and lower costs, while improving flexibility. However, the implementation of Industry 4.0 enabling technologies is a difficult task and becomes even more challenging without any standardized approach. The barriers include, but are not limited to, lack of knowledge, inability to realistically quantify the return on investment, and lack of a skilled workforce. This study presents a systematic and content-centric literature review of Industry 4.0 enabling technologies, to highlight their impact on the manufacturing industry. It also provides a strategic roadmap for the implementation of Industry 4.0, based on lean six sigma approaches. The basis of the roadmap is the design for six sigma approach for the development of a new process chain, followed by a continuous improvement plan. The reason for choosing lean six sigma is to provide manufacturers with a sense of familiarity, as they have been employing these principles for removing waste and reducing variability. Major reasons for the rejection of Industry 4.0 implementation methodologies by manufactures are fear of the unknown and resistance to change, whereas the use of lean six sigma can mitigate them. The strategic roadmap presented in this paper can offer a holistic view of phases that manufacturers should undertake and the challenges they might face in their journey toward Industry 4.0 transition.

Innovative technologies allow organizations to remain competitive in the market and increase their profitability. These driving factors have led to the adoption of several emerging technologies and no other trend has created more of an impact than Industry 4.0 in recent years. This is an umbrella term that encompasses several digital technologies that are geared toward automation and data exchange in manufacturing technologies and processes. These include but are not limited to several latest technological developments such as cyber-physical systems, digital twins, Internet of Things, cloud computing, cognitive computing, and artificial intelligence. Within the context of Industry 4.0, additive manufacturing (AM) is a crucial element. AM is also an umbrella term for several manufacturing techniques capable of manufacturing products by adding layers on top of each other. These technologies have been widely researched and implemented to produce homogeneous and heterogeneous products with complex geometries. This paper focuses on the interrelationship between AM and other elements of Industry 4.0. A comprehensive AM-centric literature review discussing the interaction between AM and Industry 4.0 elements whether directly (used for AM) or indirectly (used with AM) has been presented. Furthermore, a conceptual digital thread integrating AM and Industry 4.0 technologies has been proposed. The need for such interconnectedness and its benefits have been explored through the content-centric literature review. Development of such a digital thread for AM will provide significant benefits, allow companies to respond to customer requirements more efficiently, and will accelerate the shift toward smart manufacturing.

A number of different parts for mechanical testing were produced using composite metal foil manufacturing (CMFM). This process is a combination of laminated object manufacturing and brazing technology. Aluminium is one of the toughest metals to join and CMFM can achieve this task with ease. By using aluminium 1050 foils of 0.1 mm thickness, various parts were made according to British and International Standards, including lap joints, peel specimens, dog-bone specimens and tested for their mechanical properties. A special, 80 % zinc and 20 % aluminium by weight, brazing paste was utilized for joining the foils together. The test of the single lap joints show that none of the specimens failed at the bonded area and the failure was always due to fracture of the parent metal. Cohesive failure was also observed for the single lap joints by using 10 mm thick aluminium metal plates. It helped in calculating the lap shear strength which is a useful design parameter. The peel test showed good bond consistency in all the specimens with an average peel strength of 20 MPa. Comparative tensile test was conducted with a dog-bone specimen machined from a solid block of aluminium 1050 and specimens made with CMFM. The results showed that the specimens made by CMFM fracture at force values that are higher than that of the parent metal. This demonstrates that CMFM has the capability to produce high quality and stronger parts as compared to conventional machining methods employed for the production of metal parts. The effect of using different number of layers for the same cross-sectional area has also been investigated. Keywords Additive manufacturing Á Brazing Á Laminated object manufacturing Á Lap-shear testing Á Metal foil Á Metal parts Á Peel test Á Tensile testing & Javaid Butt

Process re-engineering and optimization in manufacturing industries is a big challenge because of process interdependencies characterized by a high failure rate. Research has shown that over 70% of approaches fail because of complexity as a result of process interdependencies during the implementation phase. This paper investigates data from a manufacturing operation and designs a filtration algorithm to analyze process interdependencies as a new approach for process optimization. The algorithm examines the data from a manufacturing process to identify limitations through cause and effect relationships and implements changes to achieve an optimized result. The proposed cause and effect approach of re-engineering is termed the Khan-Hassan-Butt (KHB) methodology, and it can filter the process interdependencies and use those as key decision-making tools. It provides an improved process optimization framework that incorporates data analysis along with a cause and effect algorithm to filter out the process interdependencies as an approach to increase output and reduce failure factors simultaneously. It also provides a framework for filtering the manufacturing data into smart structured data. Based on the proposed KHB methodology, the study investigated a production line process using the WITNESS Horizon 22 simulation package and analyzed the efficiency of the proposed approach for production optimization. A case study is provided that integrated the KHB methodology with data-driven process re-engineering to analyze the process interdependencies to use them as decision-making tools for production optimization.

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