Luisa Huaccho Huatuco

Comparing the impact of different rescheduling strategies on the entropic-related complexity of manufacturing systems

The primary objective of this paper is to compare five rescheduling strategies according to their effectiveness in reducing entropic-related complexity arising from machine breakdowns in manufacturing systems. Entropic-related complexity is the expected amount of information required to describe the state of the system. Previous case studies carried out by the authors have guided computer simulations, which were carried out in Arena 5.0 in combination with MS Excel. Simulation performance is measured by: (1) entropic-related complexity measures, which quantify: (a) the complexity associated with the information content of schedules, and (b) the complexity associated with the variations between schedules; and (2) mean flow time. The results highlight two main points: (a) the importance of reducing unbalanced machine workloads by using the least utilised machine to process the jobs affected by machine breakdowns, and (b) low disruption strategies are effective at reducing entropic-related complexity; this means that applying rescheduling strategies in order to manage complexity can be beneficial up to a point, which, in low disruption strategies, is included in their threshold conditions. The contribution of this paper is two-fold. First, it extends the application of entropic-related complexity to every schedule generated through rescheduling, whereas previous work only applied it to the original schedule. Second, recommendations are proposed to schedulers for improving their rescheduling practice in the face of machine breakdowns. Those recommendations vary according to the manufacturing organisations’ product type and scheduling objectives. Further work includes: (a) preparing a detailed workbook to measure entropic-related complexity at shop-floor level; and (b) extending the analysis to other types of disturbances, such as customer changes.

Extending the information-theoretic measures of the dynamic complexity of manufacturing systems

This paper revisits and extends the structural and dynamic complexity measures of manufacturing systems, which are based on an information-theoretic interpretation of the amount of information that is needed to describe the state of a manufacturing system. In this paper, a generic manufacturing system is modelled as a set of interacting resources and queues. At any moment in time, the combined specific states of the resources and queues define the overall state of the manufacturing system. The main contribution of this paper is a set of dynamic complexity measures that quantify the rate at which information is generated by the facility, and which may be applied with or without reference to the facilitys schedule. A worked example demonstrates the step-by-step calculations to obtain values of the complexity measures, and guidance is provided on how to obtain the data needed to carry out the calculations. The links between these complexity measures and the behaviour of a facility are identified and described.

A Method for Analysing Operational Complexity in Supply Chains

This paper proposes a method for analysing the operational complexity in supply chains by using an entropic measure based on information theory. The proposed approach estimates the operational complexity at each stage of the supply chain and analyses the changes between stages. In this paper a stage is identified by the exchange of data and/or material. Through analysis the method identifies the stages where the operational complexity is both generated and propagated (exported, imported, generated or absorbed). Central to the method is the identification of a reference point within the supply chain. This is where the operational complexity is at a local minimum along the data transfer stages. Such a point can be thought of as a ‘sink’ for turbulence generated in the supply chain. Where it exists, it has the merit of stabilising the supply chain by attenuating uncertainty. However, the location of the reference point is also a matter of choice. If the preferred location is other than the current one, this is a trigger for management action. The analysis can help decide appropriate remedial action. More generally, the approach can assist logistics management by highlighting problem areas. An industrial application is presented to demonstrate the applicability of the method.

Entropic-related complexity for re-engineering a robust supply chain: a case study

This article uses entropic-related complexity to analyse a case study of a business process re-engineering (BPR) intervention to improve the supply chain of a large UK chemicals manufacturer. Entropic-related complexity is defined as the amount of information needed to describe the state of a system; a measure which captures the extent of uncertainty and variety within the system. To evaluate BPRs impact, complexity is calculated before and after the intervention for three elements of the supply chain: incoming supply process, production process and outgoing customer delivery process. The complexity measures are derived from the time-related performance of these three system elements. The results show that the robustness of supply chains, i.e. their ability to perform well despite disturbances, can be assessed using entropic-related complexity retrospectively (after a change has occurred), but it could also be used prospectively (if anticipated outcomes could be estimated) before embarking on BPR initiatives.

Hybrid Algorithms for Service, Computing and Manufacturing Systems: Routing and Scheduling Solutions

Hybrid Algorithms for Service, Computing and Manufacturing Systems: Routing and Scheduling Solutions explores research developments and applications from an interdisciplinary perspective that combines approaches from operations research, computer science, artificial intelligence, and applied computational mathematics. Contributions cover a range of hybrid algorithm theory and practice as it relates to routing, scheduling, and real-life applications.

Supply Chain Major Disruptions and Sustainability Metrics: A Case Study

Major Disruptions and Sustainability metrics in supply chains (SCs) are presented by means of a case study involving a large manufacturing organisation. The main findings point to four main strategies which organisations could use in the face of disruptions, namely: maintaining stock, sharing information, disaster management planning, and pursuing initiatives with suppliers (e.g. dual sourcing, outsourcing, SC visibility and risk modelling). The sustainability metrics indicate that being successful at managing disruptions in SCs does not preclude manufacturing organisations from also being successful in the sustainability dimensions of the triple bottom line.

Mapping the operations and supply chain management field: a journal governance perspective

The paper addresses the research questions: how do the interlocking editorial advisory boards (EABs) of operations and supply chain (OSCM) journals map out the field’s diverse academic communities and how demographically diverse is the field and its communities? The study applies Social Network Analysis to web-based editorial advisory board data for 38 journals listed under Operations Management in the 2010 ABS academic journal quality guide. Members of editorial advisory boards of the 38 journals are divided in to seven distinct communities which are mapped to the field’s knowledge structures and further aggregated in to a core and periphery of the network. A burgeoning community of supply chain management (SCM) academics forms the core along with those with more traditional interests. Male academics affiliated to USA institutions and to business schools predominate in the sample. A new strand of research is opened up connecting journal governance networks to knowledge structures in the OSCM field. OM is studied separately from its reference and associated disciplines. The use of the ABS list might attract comments that the study has an implicit European perspective - however we do not believe this to be the case. The study addresses the implications of the lack of diversity for the practice of OM as an academic discipline. As the first study of its kind, i.e. SNA of editorial advisory board members of OSCM journals, this study marks out a new perspective and acts as a benchmark for the future.

A Systematic Literature Review on Sustainability and Disruptions in Supply Chains

The purpose of this paper is to provide the state-of-the-art of the theme: ‘sustainability and disruptions in supply chains’. The main motivation for the research was to identify the level of connectivity between these apparent separate topics and identify gaps for carrying out future research. A systematic literature review was carried out, searching the World of Science database, 76 papers were selected for analysis. The main database consulted was Web of Science for the period 2000–2016. The articles were classified according to their year of publication, country/region focus of study, citation, journal name, for example. Then the tallies of each group were collected into a MS Excel file in order to do a series of analyses, plot graphs and make comparisons. The findings point out that the International Journal of Production Economics leads the way in terms of publishing work on this theme. Most of the published work comes from North-America and Europe, however China also features highly in the ranks. The ‘sustainability’ literature included topics of: positive relation between sustainable supply chain management and economic and environmental performance. The disruptions literature included topics of: information sharing, inventory management and multiple suppliers. Some scarce combination of sustainability and disruptions was found.

Supply Chain Risk Management Identification and Mitigation: A Case Study in a Chinese Dairy Company

This study explores the risks management in the dairy supply chain in China. Using a single case study methodology, semi-structured interviews with different supply chain experts working in the dairy company were conducted. Through the interviews, data was gathered about the supply chain network of the dairy company, managers’ understanding of supply chain risks management, and risks inherent in the dairy supply chain. In general, the company has the awareness of supply chain risks and it has created an ‘organic economy business model’ which reflects its concept of supply chain risk management. However, at the operational level, the company does not have any supply chain risks management program. By following the Failure Mode Effect Analysis (FMEA) framework, the risks identified in the supply chain have been assessed and prioritized. Some recommendations have been given to mitigate the high priority risks.

Supplier Selection Processes: A Case Study in a Chinese Dairy Company

This research studies the supplier selection process in a company in the Chinese Dairy Industry. The literature review includes the food supply chain, the frameworks and models of supplier selection, the selection methods and sourcing strategies. A case study methodology including seven interviews with managers and employees was carried out. This paper discusses the similarities and differences between the research findings and literature review. It suggests the company extends the time period of the field trips to visit its potential suppliers, in order to obtain sufficient and reliable information for conducting supplier selection processes.