Press shop machine analysis and trending

Historically downtime data collection and reporting systems in many automotive body panel press shops has been somewhat adhoc. The impetus for this study stems from frustration in respect of how this data is collected, assessed for trends and presented. Ideally this data should be used to identify costly repetitious faults for actioning of maintenance work and for feedback to tool design for consideration when designing new parts.

Presently this data is stored largely in the form of tacit knowledge by press shop operators; the encumbrance of transferring such information being that there is very often only limited channels to quantify it into something more tangible. Findings show that there tend to be two related obstacles to plant data recording. The first is that automation of down time data collection alone cannot determine fault causes as the majority of press shop events are initiated primarily from operator observation. The second is that excessive subjective operator input can often result in confusion and end up taking greater time in recording than remedying the actual fault.

This Paper presents the development of a system that through press mounted touchscreens encourages basic subjective operator input and relates this with basic objective data such as timekeeping. In this way all responses for a given press line become valuable and can be trended and placed in a hierarchy based on their percentage contribution to downtime or statistical importance. This then is capable of statistically alerting maintenance, line flow and/or toolbuild areas as to what issues require their most urgent attention.

Pareto archived simulated annealing for single machine job shop scheduling with multiple objectives

In this paper, the single machine job shop scheduling problem is studied with the objectives of minimizing the tardiness and the material cost of jobs. The simultaneous consideration of these objectives is the multi-criteria optimization problem under study. A metaheuristic procedure based on simulated annealing is proposed to find the approximate Pareto optimal (non-dominated) solutions. The two objectives are combined in one composite utility function based on the decision maker’s interest in having a schedule with weighted combination. In view of the unknown nature of the weights for the defined objectives, a priori approach is applied to search for the non-dominated set of solutions based on the Pareto dominance. The obtained solutions set is presented to the decision maker to choose the best solution according to his preferences. The performance of the algorithm is evaluated in terms of the number of non-dominated schedules generated and the proximity of the obtained non-dominated front to the true Pareto front. Results show that the produced solutions do not differ significantly from the optimal solutions.

Benchmark generation algorithm for stochastic mixed model assembly shop simulation and optimization

The Operations Research (OR) community have defined many deterministic manufacturing control problems mainly focused on scheduling. Well-defined benchmark problems provide a mechanism for communication of the effectiveness of different optimization algorithms. Manufacturing problems within industry are stochastic and complex. Common features of these problems include: variable demand, machine part specific breakdown patterns, part machine specific process durations, continuous production, Finished Goods Inventory (FGI) buffers, bottleneck machines and limited production capacity. Discrete Event Simulation (DES) is a commonly used tool for studying manufacturing systems of realistic complexity. There are few reports of detail-rich benchmark problems for use within the simulation optimization community that are as complex as those faced by production managers. This work details an algorithm that can be used to create single and multistage production control problems. The reported software implementation of the algorithm generates text files in eXtensible Markup Language (XML) format that are easily edited and understood as well as being cross-platform compatible. The distribution and acceptance of benchmark problems generated with the algorithm would enable researchers working on simulation and optimization of manufacturing problems to effectively communicate results to benefit the field in general.

Solving a multiobjective job shop scheduling problem using Pareto Archived Cuckoo Search

This paper investigates a new approach for solving the multiobjective job shop scheduling problem, namely the Cuckoo Search ( CS) approach. The requirement is to schedule jobs on a single machine so that the total material waste is minimised as well as the total tardiness time. The material waste is quantified in terms of saving factors to show the reduction in material that can be achieved when producing two jobs with the same materials in sequence. The estimated saving factor is used to calculate a cost savings for each job based on its material type. A formulation of multiobjective optimisation problems is adopted to generate the set of schedules that maximise the overall cost savings and minimise the total tardiness time. where all trade-offs are considered for the two conflicting objectives. A Pareto Archived Multiobjective Cuckoo Search (PAMOCS) is developed to find the set ofnondominated Pareto optimal solutions. The solution accuracy of PAMOCS is shown by comparing the closeness of the obtained solutions to the true Pareto front generated by the complete enumeration methad. Results shaw that CS is a very effective and promising technique to solve job shop scheduling problems.

Ghosts in the machine : do the dead live on in Facebook?

Of the many ways in which identity is constructed and performed online, few are as strongly ‘anchored’ to existing offline relationships as in online social networks like Facebook and Myspace. These networks utilise profiles that extend our practical, psychological and even corporeal identity in ways that give them considerable phenomenal presence in the lives of spatially distant people. This raises interesting questions about the persistence of identity when these online profiles survive the deaths of the users behind them, via the practice of ‘memorialising’ social network profile pages. I situate these practices within a phenomenology of grief that accounts for the ways in which the dead can persist as moral patients, and show how online survival in this case illuminates an important difference between persons and selves within contemporary philosophy of personal identity. Ultimately, the online persistence of the dead helps bring into view a deep ontological contradiction implicit in our dealings with death: the dead both live on as objects of duty and yet completely cease to exist.

Clonewise - detecting package-level clones using machine learning

Developers sometimes maintain an internal copy of another software or fork development of an existing project. This practice can lead to software vulnerabilities when the embedded code is not kept up to date with upstream sources. We propose an automated solution to identify clones of packages without any prior knowledge of these relationships. We then correlate clones with vulnerability information to identify outstanding security problems. This approach motivates software maintainers to avoid using cloned packages and link against system wide libraries. We propose over 30 novel features that enable us to use to use pattern classification to accurately identify package-level clones. To our knowledge, we are the first to consider clone detection as a classification problem. Our results show our system, Clonewise, compares well to manually tracked databases. Based on our work, over 30 unknown package clones and vulnerabilities have been identified and patched.

Out of the frying pan, into the fire : Cantrills Filmnotes as Prestige Machine

This examination of the gaps and ambiguities linked to Cantrills Filmnotes (CF), an Australian publication on experimental film, offers a case study on the production and ownership of Pierre Bourdieu’s 'cultural capital' in film art at the margins, witnessed first-hand. CF emerged at the intersection between the street and the academy, spanning that period from the 70s till its abandonment in 2000 during which, it is argued here, it migrated from the former to the latter. This examination surveils, in retrospect, for whose benefit was the magazine's accumulation of power, status and prestige exercised, in whose service was it exacted? CF’s manifesto-like editorial rhetoric was often directed at perceived shortcomings of those institutions servicing film art in Australia. What is revealed when such a critical eye focuses on the production of Cantrills Filmnotes (CF) itself? CF's cultural production has a further dimension of both taking on and taking place inside a colonial mind-set, a cultural cringe often the subject of editorial commentary, elucidating a practice residing at the geographic margins of a marginal arts practice. The founders and editors of CF, the married couple Corinne and Arthur Cantrill both suffered and benefited from CF’s impact on this international field of art production.

A multiobjective state transition algorithm for single machine scheduling

In this paper, a discrete state transition algorithm is introduced to solve a multiobjective single machine job shop scheduling problem. In the proposed approach, a non-dominated sort technique is used to select the best from a candidate state set, and a Pareto archived strategy is adopted to keep all the non-dominated solutions. Compared with the enumeration and other heuristics, experimental results have demonstrated the effectiveness of the multiobjective state transition algorithm.

A machine-driven process for human limb length estimation using inertial sensors

The computer based human motion tracking systems are widely used in medicine and sports. The accurate determination of limb lengths is crucial for not only constructing the limb motion trajectories which are used for evaluation process of human kinematics, but also individually recognising human beings. Yet, as the common practice, the limb lengths are measured manually which is inconvenient, time-consuming and requires professional knowledge. In this paper, the estimation process of limb lengths is automated with a novel algorithm calculating curvature using the measurements from inertial sensors. The proposed algorithm was validated with computer simulations and experiments conducted with four healthy subjects. The experiment results show the significantly low root mean squared error percentages such as upper arm - 5.16%, upper limbs - 5.09%, upper leg - 2.56% and lower extremities - 6.64% compared to measured lengths.