Lean implementation involves eliminating all forms of waste (for example, defects or overproduction) and consists of many improvement strategies or systems such as mistake proofing (Poka-Yoke) and Single Minute Exchange of Die (a.k.a. quick changeover). The purpose of this study is to discuss a successful lean or waste elimination initiative for a building products company. Specifically, this study describes how mistake proofing and quick changeover systems were implemented using soft OR practices or Soft Systems Methodology (SSM). Essentially, SSM consisted of four sequential stages, namely (1) problem identification, (2) basic approaches to improvement, (3) making plans for improvement, and (4) translating improvement plans into reality. The study contributes in two ways: for practicing managers, it shows that at the core of lean is soft OR practices, and for academicians, it provides directions for future research.
Many post-secondary academic institutions in the United States have a First-Year Seminar Program. These seminars are designed to support the success of new incoming first-year students by combining writing, research and active discussion among small groups of students. At Dickinson College, students are required to select six seminars they find interesting from a list of approximately 42 seminars. The college then attempts to assign each student to a seminar on their list, while maintaining course capacities. Using standard commercial optimization software, we develop an approach that not only solves this basic assignment problem, but also seeks to balance both the gender and number of international students in the seminars. In addition, we utilize Monte Carlo simulation to study how the number of seminars each student is required to select affects the likelihood that a feasible assignment exists.
(2013). Exploring alternative routes to realising the benefits of simulation in healthcare. OR Insight: Vol. 26, No. 1, pp. 1-4.
Military Operations Research studies often involve the analysis of structured descriptions of plausible contingencies called ‘scenarios’. While scenarios attempt to provide a sufficient account of an unfolding contingency they do not typically include details of specific types of missions undertaken at the operational level or even the broad roles of the military forces undertaking those missions. Some means of linking key events, decision points and military activities in the chosen scenario to the roles and missions undertaken by a military force was thus sought for recent studies in joint operations. This article discusses a Mission-to-Scenario methodology developed, which provides a repeatable framework to structure the analysis of related problems. Application of the Mission-to-Scenario methodology for military macro-system analysis may then be used to explore the efficacy of military capabilities, operational effectiveness of specific platforms and the impact of proposed insertion of new technologies or organisational changes.
In the United Kingdom, passenger cars are the largest contributor to green house gas (Carbon dioxide (CO2)) emissions from road transport. Estimates of CO2 emissions (and associated fuel consumption) are mainly based on data obtained from the rolling road testing of new car models as managed by the Vehicle Certification Agency. The main outputs of this testing for each car model are the expected CO2 emissions in g/km and the expected overall miles per gallon achievable. There are three main areas of concern addressed in this article – that the car emission testing procedures do not accurately reflect outputs achievable under normal on-the-road driving conditions, that the test outputs are used directly by government in building green house gas inventories and that the reported test outputs for individual car models are misleading in relation to car purchasing decisions. The article in particular challenges the current UK fleet estimates reported by the Department for Energy and Climate Change that, it is argued, are likely to be significant underestimates. The main aims have been to model the required adjustments of emission factors derived from rolling road tests in order to account for on-the-road effects. Results are compared and contrasted with official governmental estimates.
Risk Management (RM) is rapidly evolving; its practitioners are increasingly shifting focus from pure operational or financial risks to a broader Enterprise Risk Management (ERM). ERM involves a set of processes and methods used to manage risks that are not just associated with accidental losses but also associated with financial, strategic, technological and other business areas. This article highlights different factors that affect the adoption of ERM which include people’s perception of RM and the necessity for a risk-aware culture at all levels within organisations before adopting the ERM-based approach. The article also addresses a few popular ERM frameworks that help organisations to understand a complete picture of ERM activities and its functional areas. The work presented in this article is taken from an on-going project that is being undertaken to develop a practical tool for providing better analysis of risk data and improved knowledge management.
Accurate demand forecasting is crucial for companies, since both overage and shortage of products can reduce company profits. Numerous statistical measures have been proposed to evaluate the accuracy of forecasts, but these measures tend to neglect the different economic impact of forecast errors for different items. Motivated by industry practitioners’ need to evaluate their forecasting processes and identify potentials for improvement, we develop a framework to evaluate demand forecasts. The framework consists of statistical measures and a scoring model and allows for an analysis of forecast accuracy on different levels of aggregation. A case study from a large retailing company shows that the framework is easy to implement in standard software and can provide relevant managerial insights.
A medieval document in Exeter Cathedral Library includes a page that lists people and property in the South-West of Devon. It appears to show the route of a 14-day journey taken by a clergyman acting as the confessor for the parishioners. If so, it is the only extant evidence for the practice of such a confessor visiting the homes of the parish rather than the parishioners attending the church. This article examines the list and offers evidence that supports the belief that the clergyman made the mapped journey, although it cannot be proved that it took him 14 days, or that he heard confessions during it.
Spreadsheets are ubiquitous in modern organizations. However, most of the tasks they are used for would be better served by more specialist applications. In this article, we highlight some of the abuses of spreadsheets – and the consequences. We explain why spreadsheets are inappropriate in many corporate situations and point readers to alternatives. Finally, we note that spreadsheets do have a very important role to play – as tools for prototyping.
An outpatient pharmacy of a tertiary hospital in Singapore had uncertainty over the impact of different manpower scheduling strategies on the length of time (that is, cycle time) that their patients needed to spend during their visits. This article illustrated how this uncertainty could be addressed via application of discrete-event simulation (DES). Recent service rates of pharmacy staff and manpower allocation schedules were used to represent the process characteristics of the pharmacy in a DES model. On the basis of different new manpower scheduling strategies, the DES model projected quantitatively their respective impact on patient cycle times and manpower resource requirements. In this study, a new manpower scheduling plan, which matched manpower availability with patient arrival pattern, was recommended. On the basis of DES model projections, this recommendation could reduce both median and 95th percentile cycle times (39.7–45.7 per cent) with less than 7.5 per cent increase (or two new hires) in overall manpower requirement.
This study presents empirical evidence on the relationship between the forecast errors and the number of individual forecasts used in averages of model forecasts. The investigation is based on forecasts published by Her Majesty's Treasury in the monthly report 'Forecasts for the UK economy: A comparison of independent forecasts'. The results suggest that averages of model forecasts tend to improve forecasting performance when relatively large numbers of forecasts are used in the averages (usually in excess of 40); however, results are not always consistent and averages should be used with caution.
In this article we present a Vehicle Routing Problem (VRP) faced by a large distribution company in the Northeast of Spain. The company distributes products from its central facilities to a chain of around 400 stores all over the country. One of the peculiarities of the VRP of this company – which is common among real-life VRPs – is the presence of a heterogeneous fleet where vehicles with different capacities can make multiple trips during a single day. This variant of the problem, which we refer as Heterogeneous Fleet and Multi-trip VRP, has been barely studied in the literature. To solve the problem, we use an algorithm based on the well-known savings heuristic with a biased-randomization effect and three local search operations. Our approach is simple to implement as it needs few parameters and no fine-tuning processes, which are usually cumbersome and require experts' involvement. We obtain savings of around 12 per cent in transportation costs, which represent around €30 000 saved per week.
Judgement-based (or ‘soft’) Operational Research (OR) is used in Defence, although it may not be well known and understood and it may not be perceived to have the rigour of more quantitative techniques. A NATO task group was set up to address these features and to produce a Code of Best Practice with the purpose of: creating an understanding of judgement-based OR, clarifying when and how it can be used, and providing guidance on how the critical features of validity, credibility and acceptance can be achieved. Two distinct volumes were produced: one directed towards the analysts and the other towards the clients. We propose that a sound process be followed with due diligence and that this will provide the evidence needed to protect the client from criticism. The article describes the motivation behind the project, the products and some reflections on judgement-based OR.
This article outlines a four-step approach in analysing a complex supply chain using optimization and simulation software tools. The first step consists of Multi-Echelon Optimization to determine the best supply chain structures. The second step involves a Discrete-Event Simulation to determine the appropriate supply chain configuration. The third step, Simulation-Optimization , is then used to improve the supply chain's design established in the first two steps by optimizing the policies used to govern the network's behaviour. The final step, Design for Robustness , ensures that the final selection of the supply chain's network structure and policies will operate well under a wide variety of situations by minimizing the risk of undesirable outcomes. Using a four-step methodology, supply chain modelling provides an efficient supply chain design operating under effective inventory, sourcing and transportation policies. A case study from a Fortune 500 manufacturing company is evaluated using the four-step methodology. Future studies are outlined.
A variety of different assessment formats has evolved in higher education in recent years – many inspired by task-related activities in the working environment. Some are not new: at Masters level, the dissertation is long-established, whereas at undergraduate level, projects and portfolios are proving increasingly popular. Portfolios are particularly favoured for professional subjects. Implementing these alternative forms of assessment is not always straightforward even when strict rubrics are applied. As a consequence, double-marking is frequently used in an effort to reduce the subjectivity of marks awarded. Unfortunately, this strategy too can prove problematic – as recent studies have shown – especially when there is an irreconcilable disagreement between first and second examiners. In the article, we focus on this issue of inter-marker conflict and through a series of simple statistical models offer insights into how final marks might more fairly be determined.
This article introduces the subject of terrorism and counter-terrorism by means of a two-person bimatrix game that provides some insight into the behaviour of the two players. We then examine three important areas in counter-terrorism tasks: the detection of terrorist cells and how to render them inoperable, the fortification of assets in order to protect them from terrorist attacks and the optimal evacuation of people from an area affected by terrorism. Basic mathematical models are formulated and demonstrated. This article concludes with some thoughts on potential extensions of the models presented here.
In this article, we address a variant of the rolling stock (RS) problem in dense railway systems within a metropolitan context. It consists in determining every train composition and scheduling empty trains to efficiently fit the demand. By empty trains we refer to scheduled trips where trains travel along the system without carrying passengers. A heuristic is presented to generate eligible slots for empty trains.Two objective functions are considered: minimizing the amount of RS and minimizing its usage (number of kilometres). An illustrative case study corresponding to the C5 line of a Spanish railway is presented.
This study presents a Decision Support Tool (DST) for managing tankers on-site at a Pharmaceutical Company. The objective of the DST is to minimize the operational costs related to receiving solvents and disposing waste by optimizing the decisions made by the yard manager considering the manufacturing, quality control and traffic departments. On the basis of the empirical data, it is concluded that the DST increased the dam utilization by 17 per cent, and reduced the total (move and delay) costs by 19 per cent, the total movements by the internal truck operator by 34 per cent, and the yard logistics operator duties by approximately 60 per cent. The DST can also be used as a tool to optimize the supply chain by improving the scheduling and to determine the number of dam spaces required, which has direct environmental implications. The simplicity of the tool and the quality of the results prompted interest from our industrial collaborator to implement the DST.
