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Krisztina Demeter, Levente Szász, Béla-Gergely Rácz and Lehel-Zoltán Györfy
The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly…
Abstract
Purpose
The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly, business performance. With the emergence of Industry 4.0 (I4.0) technologies, manufacturing companies can use a wide variety of advanced manufacturing technologies (AMT) to build an efficient and effective production system. Nevertheless, the literature offers little guidance on how these technologies, including novel I4.0 technologies, should be combined in practice and how these combinations might have a different impact on performance.
Design/methodology/approach
Using a survey study of 165 manufacturing plants from 11 different countries, we use factor analysis to empirically derive three distinct manufacturing technology bundles and structural equation modeling to quantify their relationship with operations and business performance.
Findings
Our findings support an evolutionary rather than a revolutionary perspective. I4.0 technologies build on traditional manufacturing technologies and do not constitute a separate direction that would point towards a fundamental digital transformation of companies within our sample. Performance effects are rather weak: out of the three technology bundles identified, only “automation and robotization” have a positive influence on cost efficiency, while “base technologies” and “data-enabled technologies” do not offer a competitive advantage, neither in terms of cost nor in terms of differentiation. Furthermore, while the business performance impact is positive, it is quite weak, suggesting that financial returns on technology investments might require longer time periods.
Originality/value
Relying on a complementarity approach, our research offers a novel perspective on technology implementation in the I4.0 era by investigating novel and traditional manufacturing technologies together.
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Alessandro Tufano, Riccardo Accorsi and Riccardo Manzini
This paper addresses the trade-off between asset investment and food safety in the design of a food catering production plant. It analyses the relationship between the quality…
Abstract
Purpose
This paper addresses the trade-off between asset investment and food safety in the design of a food catering production plant. It analyses the relationship between the quality decay of cook-warm products, the logistics of the processes and the economic investment in production machines.
Design/methodology/approach
A weekly cook-warm production plan has been monitored on-field using temperature sensors to estimate the quality decay profile of each product. A multi-objective optimisation model is proposed to (1) minimise the number of resources necessary to perform cooking and packing operations or (2) to maximise the food quality of the products. A metaheuristic simulated annealing algorithm is introduced to solve the model and to identify the Pareto frontier of the problem.
Findings
The packaging buffers are identified as the bottleneck of the processes. The outcome of the algorithms highlights that a small investment to design bigger buffers results in a significant increase in the quality with a smaller food loss.
Practical implications
This study models the production tasks of a food catering facility to evaluate their criticality from a food safety perspective. It investigates the tradeoff between the investment cost of resources processing critical tasks and food safety of finished products.
Social implications
The methodology applies to the design of cook-warm production. Catering companies use cook-warm production to serve school, hospitals and companies. For this reason, the application of this methodology leads to the improvement of the quality of daily meals for a large number of people.
Originality/value
The paper introduces a new multi-objective function (asset investment vs food quality) proposing an original metaheuristic to address this tradeoff in the food catering industry. Also, the methodology is applied and validated in the design of a new food production facility.
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Dr Panayiotis Ketikidis, Dr S.C. Lenny Koh and Dr Angappa Gunasekaran
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