A transformation of human operation approach to inform system design for automation

Design of automation system relies on experts’ knowledge and experience accumulated from past solutions. In designing novel solutions, however, it is difficult to apply past knowledge and achieve design right-first-time, therefore wasting valuable resources and time. SADT/IDEF0 models are commonly used by automation experts to model manufacturing systems based on the manual process. However, function generalisation without benchmarking is difficult for experts particularly for complex and highly skilled-based tasks. This paper proposes a functional task abstraction approach to support automation design specification based on human factor attributes. A semi-automated clustering approach is developed to identify key functions from an observed manual process. The proposed approach is tested on five different automation case studies. The results indicate the proposed method reduces inconsistency in task abstraction when compared to the current approach that relies on the experts, which are further validated against the solutions generated by automation experts.</p

Uncertainty perception in bidding for Product-Service Systems under competition

This research investigates what impact of uncertainty perception arising from the existence of competition has on the pricing decision for Product-Service Systems (PSS) under uncertainty. PSS provision is an increasingly important area for many businesses and competition increases cognitive pressures on providers even further. We present an experimental study with industrial costing and bidding experts from the defence and aerospace sector. The study consisted of an experimental set-up via two questionnaires which differed in the existence of competition in the bidding scenario. The findings showed that bidding decision makers changed their evaluation of the cost estimate due to the introduction of competition but kept their evaluations of the profit margin and price bids constant. Furthermore, the participants listed the relevant sources of uncertainty that influenced their decision-making process. This research contributes to the literature in two ways. First, our findings showed that predictions from current theory regarding decision-making of cost estimation and pricing are not confirmed when competitively bidding for PSS. Second, we show uncertainty sources that influenced the decision makers and identified p the importance of internal processes of the PSS provider and environmental uncertainty.</p

Uncertainty perception in bidding for Product-Service Systems under competition

This research investigates what impact of uncertainty perception arising from the existence of competition has on the pricing decision for Product-Service Systems (PSS) under uncertainty. PSS provision is an increasingly important area for many businesses and competition increases cognitive pressures on providers even further. We present an experimental study with industrial costing and bidding experts from the defence and aerospace sector. The study consisted of an experimental set-up via two questionnaires which differed in the existence of competition in the bidding scenario. The findings showed that bidding decision makers changed their evaluation of the cost estimate due to the introduction of competition but kept their evaluations of the profit margin and price bids constant. Furthermore, the participants listed the relevant sources of uncertainty that influenced their decision-making process. This research contributes to the literature in two ways. First, our findings showed that predictions from current theory regarding decision-making of cost estimation and pricing are not confirmed when competitively bidding for PSS. Second, we show uncertainty sources that influenced the decision makers and identified p the importance of internal processes of the PSS provider and environmental uncertainty

Stakeholder perspectives on the cost requirements of Small Modular Reactors

The cost of a nuclear power plant (NPP) is an important influence on the future commercial success of Small Modular Reactors (SMRs). At the early design stage, the cost requirements of SMRs can be derived from an analysis of the factors driving the Levelized Cost of Electricity (LCOE). It is often much later into the development process before customers are engaged and their cost requirements are known, by which time key design decisions which influence the lifecycle cost have already been locked-in. A clear understanding is required of the cost priorities for the key stakeholders who are to invest in the SMR. This paper presents a novel approach to ranking the relative importance of different cost factors used to calculate the LCOE. Using a dynamic stakeholder analysis, the key decision-makers for each stage of the SMR product lifecycle are identified. The Analytic Hierarchy Process (AHP) with pair-wise comparisons obtained from nuclear cost experts is employed to rank the different factors in terms of their relative importance on the commercial success of a near-term deployable SMR. Each expert provides a different set of rankings, although project financing cost is consistently the most important for the successful commercial deployment of the SMR. The approach presented in this paper can be used as a verification method for any power generation technology to provide confidence that cost requirements are adequately captured to design for life cycle cost competitiveness from the perspective of different stakeholders.</p

Stakeholder perspectives on the cost requirements of Small Modular Reactors

This paper is in closed access until 11th Dec 2019.© 2018 Elsevier Ltd The cost of a nuclear power plant (NPP) is an important influence on the future commercial success of Small Modular Reactors (SMRs). At the early design stage, the cost requirements of SMRs can be derived from an analysis of the factors driving the Levelized Cost of Electricity (LCOE). It is often much later into the development process before customers are engaged and their cost requirements are known, by which time key design decisions which influence the lifecycle cost have already been locked-in. A clear understanding is required of the cost priorities for the key stakeholders who are to invest in the SMR. This paper presents a novel approach to ranking the relative importance of different cost factors used to calculate the LCOE. Using a dynamic stakeholder analysis, the key decision-makers for each stage of the SMR product lifecycle are identified. The Analytic Hierarchy Process (AHP) with pair-wise comparisons obtained from nuclear cost experts is employed to rank the different factors in terms of their relative importance on the commercial success of a near-term deployable SMR. Each expert provides a different set of rankings, although project financing cost is consistently the most important for the successful commercial deployment of the SMR. The approach presented in this paper can be used as a verification method for any power generation technology to provide confidence that cost requirements are adequately captured to design for life cycle cost competitiveness from the perspective of different stakeholders

Uncertainty in competitive bidding:A framework for product-service systems

Owing to servitisation, manufacturing companies are increasingly required to compete through the provision of services around their products. The contracts for these services are often allocated through competitive bidding where the potential suppliers submit a price bid to the customer. The pricing decision is influenced by various uncertainties. This article proposes a conceptual framework depicting these influencing uncertainties on the bidding strategy. This framework is based on three empirical studies with industry investigating different viewpoints on the decision-making process. The intention is to support the pricing decision when competitively bidding for a service contract. The framework can be applied to specific competitive bidding situations to identify the influencing uncertainties, model them and depict their influences on the pricing decision

Application of a Multivariate Process Control Technique for Set-Up Dominated Low Volume Operations

In traditional high-volume manufacturing applications, the timing of control adjustments to processes is based on parametric Statistical Process Control (SPC) methods, such as Shewhart X & R charts. In high-value, high-complexity and low-volume industries, where production runs are in the order of tens rather than thousands, traditional SPC approaches are not easily applicable. A manufactured component's complexity, with multiple critical features to monitor, increases the difficulty for a process operator to maintain all of them within their design tolerances. In response to this, this paper presents a framework of nonparametric SPC, called multivariate Set-Up Process Algorithm (mSUPA), for managing control adjustment when required. mSUPA uses a simple to interpret traffic light system for alerting process operators when an adjustment is required. mSUPA is underpinned by multivariate statistics and probability theory for validating a process set up. The case of mSUPA application to a real industry process is discussed