Abstract

Abstract
In the pursuit of increasing efficiency, productivity and flexibility at production lines and their corresponding workstations, manufacturing companies have started to heavily invest in "collaborative workspaces" where close interaction between humans and robots promises to lead to these goals that neither can achieve on their own. Therefore, it is necessary to know the contributions, recommendations and guidelines that literature presents in terms of designing a manufacturing workplace where humans and cobots interact with each other to accomplish the defined objectives. These aspects need to be explored in an integrated and multidisciplinary way to maximize human involvement in the decision chain and to promote wellbeing and quality of work. This paper presents a systematic literature review on designing human-robot collaboration (HRC) workspaces for humans and robots in industrial settings. The study involved 252 articles in international journals and conferences proceedings published till 2019. A detailed selection process led to including 65 articles to further analysis. A framework that represents the complexity levels of the influencing factors presented in human-robot interaction (HRI) contexts was developed for the content analysis. Based on this framework the guidelines and recommendations of the analysed articles are presented in three categories: Category 1 - the first level of complexity, which considers only one specific influencing factor in the HRI. This category was split into two: human operator, and technology; Category 2 - the second level of complexity, includes recommendations and guidelines related to human-robot team's performance, and thus several influencing factors are present in the HRI; and, finally, Category 3 - the third level of complexity, where recommendations and guidelines for more complex and holistic approaches in the HRI are presented. The literature offers contributions from several knowledge areas capable to design safe, ergonomic, sustainable, and healthy human-centred workplaces where not only technical but also social and psychophysical aspects of collaboration are considered.

Abstract
Paper aims: This study analyzes the comprehension of production engineering students about the influence of some key variables on the process performance measures in a service process, Originality: This paper points out the need for educators to re-evaluate their approaches to teaching the Operations Management (OM) principles related to process flow measures, Research method: This study used scenario-based role-playing experiments with 2×2×2 between-subject factorial design with three independent variables (variability of activities, capacity utilization, and resource pooling) and four dependent variables related to key internal process performance measures (Flow Time, Overall Quality of service, Quality of service employees, and Queue Size), The sample was composed of 178 undergraduate production engineering students from a large university in Brazil from various institution units, Main findings: These results show that students perceived the use of resource pooling as an impactful practice, However, the students did not correctly identify the effects of increasing resource utilization and the variability on flow time and queue size when activities are pooled, Implications for theory and practice: The teaching of basic concepts of OM requires the support of computational tools, Undergraduate courses that contemplate subjects in the field of OM should work more intensely on simulation-based learning.

Abstract
While Industry 4.0 promises large technological improvements, firms face multiple challenges in its adoption. Current literature has made significant efforts to identify the barriers which are common to most companies but fails to identify their interrelationships and their implications for practitioners. We use interpretive structural modelling (ISM) methodology to identify these barriers and their interrelationships, combined with matrix impact of cross multiplication applied to classification (MICMAC) analysis to identify the root barriers, in the context of the Portuguese manufacturing industry. We categorize these barriers using the Technology -Organization-Environment framework. We conclude that barriers related to standardization and lack of off -the-shelf solutions are considered root barriers. Our results differ from other studies that regard barriers related to legal and contractual uncertainty with the highest driving power and lowest dependence power. Also, we find that organizational barriers have the highest dependency and lowest driving power, contradicting studies on the topic. We provide recommendations for managers and policymakers in three areas: Standardization Dissemination, Infrastructure Development, and Digital Strategy.

Abstract
We study a variant of the Probabilistic Travelling Salesman Problem arising when retailers crowdsource last-mile deliveries to their own customers, who can refuse or accept in exchange for a reward. A planner must identify which deliveries to offer, knowing that all deliveries need fulfilment, either via crowdsourcing or using the retailer's own vehicle. We formalise the problem and position it in both the literature about crowdsourcing and among routing problems in which not all customers need a visit. We show that to evaluate the objective function of this stochastic problem for even one solution, one needs to solve an exponential number of Travelling Salesman Problems. To address this complexity, we propose Machine Learning and Monte Carlo simulation methods to approximate the objective function, and both a branch-and-bound algorithm and heuristics to reduce the number of evaluations. We show that these approaches work well on small size instances and derive managerial insights on the economic and environmental benefits of crowdsourcing to customers.

Abstract
To transform an organization, it isn't possible to ignore the people aspect and the significant impact of talent development in any transformation process. While in larger organizations, there is often access to more resources that ultimately could bring the needed competencies to successfully run such a complex program, in small or medium enterprises, the resources are more limited and the access to talent more difficult, forcing a potential more aggressive strategy in developing the digital skills needed to enable their transformation. This work aims to review some of the literature and better comprehend the role of learning analytics as a practice that could potentially be used to enhance the learning process within Small and Medium Enterprises and support the improvement of digital literacy within these companies.