Towards a Framework for Smart Manufacturing adoption in Small and Medium-sized Enterprises

Smart Manufacturing (SM) paradigm adoption can scale production with demand without compromising on the time for order fulfillment. A smart manufacturing system (SMS) is vertically and horizontally connected, and thus it can minimize the chances of miscommunication. Employees in an SME are aware of the operational requirements and their responsibilities. The machine schedules are prepared based on the tasks a machine must perform. Predictive maintenance reduces the downtime of machines. Design software optimizes the product design. Production feasibility is checked with the help of simulation. The concepts of product life cycle management are considered for waste reduction. Employee safety, and ergonomics, identifying new business opportunities and markets, focus on employee education and skill enhancement are some of the other advantages of SM paradigm adoption. This dissertation develops an SM paradigm adoption framework for manufacturing SMEs by employing the instrumental research approach. The first step in the framework identified the technical aspects of SM, and this step was followed by identifying the research gaps in the suggested methods (in literature) and managerial aspects for adopting SM paradigm. The technical and the managerial aspects were integrated into a toolkit for manufacturing SMEs. This toolkit contains seven modular toolboxes that can be installed in five levels, depending on an SME’s readiness towards SM. The framework proposed in this dissertation focuses on how an SME’s readiness can be assessed and based on its present readiness what tools and practices the SMEs need to have to realize their tailored vision of SM. The framework was validated with the help of two SMEs cases that have recently adopted SM practices

Systematic Steps Towards Concept Design of Pay–per-X Business Models : An Exploratory Research

During the last decade, equipment manufacturing companies (EMIs) have increasingly understood the unique competitive advantages offered by Pay-per-X (PPX) business models (BMs). Many such EMI companies seem ready for the transition towards PPX BMs. However, they are not aware of the needed systematic steps that will help them in the concept design of PPX models. There are currently no available systematic PPX concept design processes and related steps in literature that can support EMI companies in identifying their relevant PPX BM options. Therefore, we make use of qualitative case study research method and identify such overall process and major steps with the help of interviews and workshops with a company that has successfully designed and identified their PPX models. Additionally, these design steps are validated with the help of 3 companies that plan to shift towards offering PPX models.acceptedVersionPeer reviewe

Review of PPX Business Models : Adaptability and Feasibility of PPX Models in the Equipment Manufacturing Industry

The overall purpose of this study is to understand how manufacturing companies have so far made use of and can make use of pay-per-x (PPX) business models (BMs) largely in capital product markets, and which mechanisms have helped them in the implementation. Through systematic literature approach this study analysed 14 research publications which exclusively focused on PPX business models. The differences between PPX business model patterns were studied from three perspective, namely criticality of product, need of process knowledge and complexity of the process and its output. We find out that the pay-per-outcome business model, is more prevalent for products which are critical, needs extensive process knowledge and are rather complex. In contrarily, pay-per-output business model is more prevalent when these conditions are not met. However, none of these three factors prevents implementing other type of PPX business model but rather specific business model is more feasible when specific conditions are met. This paper contributes a much more in-depth qualitative view on the patterns and related qualitative arguments for the useful application of PPX models in equipment manufacturing industries and helps to understand the differences between PPX business model types.acceptedVersionPeer reviewe

Digitalized manufacturing logistics in engineer-to-order operations

This is a post-peer-review, pre-copyedit version of an article published in Advances in Production Management Systems. Production Management for the Factory of the Future. APMS 2019. IFIP Advances in Information and Communication Technology, vol. 566. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-30000-5_71. The high complexity in Engineer-To-Order (ETO) operations causes major challenges for manufacturing logistics, especially in complex ETO, i.e. one-of-a-kind production. Increased digitalization of manufacturing logistics processes and activities can facilitate more efficient coordination of the material and information flows for manufacturing operations in general. However, it is not clear how to do this in the ETO environment, where products are highly customized and production is non-repetitive. This paper aims to investigate the challenges related to manufacturing logistics in ETO and how digital technologies can be applied to address them. Through a case study of a Norwegian shipyard, four main challenges related to manufacturing logistics are identified. Further, by reviewing recent literature on ETO and digitalization, the paper identifies specific applications of digital technologies in ETO manufacturing. Finally, by linking manufacturing logistics challenges to digitalization, the paper suggests four main features of digitalized manufacturing logistics in ETO: (i) seamless, digitalized information flow, (ii) identification and interconnectivity, (iii) digitalized operator support, and (iv) automated and autonomous material flow. Thus, the paper provides valuable insights into how ETO companies can move towards digitalized manufacturing logistics

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Rank-based memetic algorithm for capacitated arc routing problems

The Capacitated Arc Routing Problem (CARP) has gathered a lot of interest lately. It has a wide range of applications in real world problems, such as waste collection, winter gritting, postal delivery, etc. A number of different algorithms have been proposed to efficiently solve this problem. As CARP is an NP-hard problem, heuristic and meta-heuristic approaches are adopted for medium to large-scale problems. Memetic algorithms are of particular interest with respect to CARP. In 2001, Lacomme introduced a memetic algorithm (known as the LMA) to solve this NP-hard problem, which proved to be an effective approach to solve this problem. Yi Mei et al. further improved this to the Improved LMA (ILMA). Tang et al. proposed a memetic algorithm that scans the extended neighborhood in search for better solutions, using the Merge-Split operator. From the study of these algorithms (and memetic algorithms in general), it is clear that local search is one of the key factors distinguishing algorithm performance. Parameters of local search such as step size play an important role in determining the quality of the solution, and the computational cost of the algorithm. Keeping that in mind, this project looks at a Rank Based Memetic Algorithm that suggests a new edge selection criteria for local search, and also improves the capability of the search operation to search within a larger neighborhood, thereby discovering new search schemas within the scope of local search itself. The proposed Rank-based Neighborhood Search operator can search for solutions in a larger neighborhood, which can then be refined using the classical local search operators. This algorithm has been tested on seven benchmark test sets for CARP, and it outperforms several state-of-the-art algorithms.Bachelor of Engineering (Computer Engineering