Actual Processing Time Research Articles

Process time distribution simulation in robotic assembly line balancing

Feedback control systems utilised in car body construction cause process time variance when compensating for external disturbances. By considering these in robotic assembly line balancing, the risk of cycle time violations can be controlled. This requires knowledge of the underlying process time distributions, which are not known in advance. Therefore, a simulation method is proposed to assess the impact of varying process time distributions on the balancing of robotic assembly lines. The initial step involves acquiring the process times of existing production processes. In the subsequent simulation, these are randomly and repeatedly selected as substitutes for the process times in the balancing of a new robotic assembly line. The impact of process time distribution variations on the result is investigated, and a single solution can be selected. The proposed method is evaluated based on the balancing of a robotic assembly line for a body-in-white rear compartment. Results are compared to normally distributed process times, which is a common assumption for modelling uncertain process times. Both approaches are evaluated utilising actual process time distributions. It is demonstrated that the proposed method yields fewer and less severe underestimations of cycle times, thereby reducing the number of uncontrolled violations of cycle times.

Evaluation of an operating durian shell charcoal briquette manufacturing line and development of a biorefinery process for higher value products

In assessing the feasibility of carbonization for the treatment of durian shell, a large-scale (10 T) fuel briquette manufacturing line is evaluated, taking into consideration the actual processing time and the effect of the biomass high moisture content on overall efficiency. The fuel product exhibits a high higher heating value (HHV) (33.21 MJ/kg) but with a low production efficiency (10 %) and a high cost of production (0.55 USD/kg briquette). One alternate biorefinery process was proposed to turn durian shells into much higher value materials, including high-methoxyl pectin (DE > 90 %), high surface area activated carbon (>300 m2/g) and mineral-rich biochar, with higher recovery efficiency and selling prices, most notably pectin at 40 USD/kg. The results from this study are then used to provide recommendations for feasible treatment, not only for durian shells but also for a variety of different complex and highly recalcitrant biomass in pursuit of a more sustainable agricultural production.

Single-Machine Maintenance Activity Scheduling with Convex Resource Constraints and Learning Effects

In this paper, the single-machine scheduling problems under the common and slack due date assignments are studied, where the actual processing time of the job needs to consider some factors, such as convex resource allocation, maintenance activity, and learning effects. The goal of this study is to find the optimal sequence, maintenance activity location, resource allocation and common due date (flow allowance). The objective function is (1) to minimize the sum of scheduling cost (including the weighted sum of earliness, tardiness and common due date (flow allowance), where the weights are position-dependent weights) and resource consumption cost, and (2) to minimize the scheduling cost under the resource consumption cost which is bounded. We prove that these problems can be solved in polynomial time.

Single machine SLK/DIF due window assignment problem with general job-dependent positional effect and outsourcing operations

This paper considers the SLK/DIF due window assignment problems on a single machine with a general job-dependent positional effect, where the actual processing time of a job is subject to a job-dependent and positional effect. Production schedulers may decide to outsource/reject some jobs by paying the corresponding costs. Based on whether to accept the tardiness jobs, we consider two different objectives under slack and different due window assignment, respectively. The first objective function is to minimize the weighted sum of earliness, tardiness, due window starting time, due window size, and outsourcing costs, while the second objective function is to minimize the cost function that includes earliness, due window starting time, due window size and outsourcing costs. We study the structural properties of two due window assignment methods and develop polynomial-time solution algorithms for the considered problems. A numerical example proves the advantage of the outsourcing decision and the distinction between two different objectives.

IMPROVING THE FISHERY BUSINESS PERMIT ISSUANCE USING BUSINESS PROCESS IMPROVEMENT

This study aims to analyse the actual business process applied in the Capital Investment Agency and One-Stop Licensing Centre of Aceh Province, mainly on issuing a fishery business permit. The institution has established 240 working hours (equivalent to 14,400 minutes) to issue the permit based on the SOP (standard operating procedures). However, a field observation showed that the actual process time exceed up to 600 hours (equivalent to 37,104 minutes). To investigate the gap and analyse the business process activities, this study employs Business Process Improvement (BPI) which consists of phase 1: organizing for improvement, phase 2: understanding the process, and phase 3: streamlining. This study occupies Bizagi Modeler to build and simulate a systematic business process model according to Business Process Modelling and Notation (BPMN). Based on the simulation process, the actual business process resulted 110 activities with total time 37,104 minutes, while the redesign model resulted 72 activities with total time 197.25 working hours (equivalent to 11,835 minutes). The redesign model further measured using devil’s quadrangle and obtained 68.11% efficiency. The efficiency aligns with better flexibility and service quality improvement.

Implementing Time-Driven Activity-Based Costing for Unused Capacity Measurement in Local University

All university departments must maximize their use of time and resources in order to meet their goal with the least amount of waste. The existing system in a local university does not implement the time equation and so the processing time determined is not in accordance with the actual processing time of every activity. Thus, the present implementation in the organization does not illustrate the correlation between the supplied resources and the practical capacity. The purpose of this study was to build a new costing structure using time-driven activity-based costing for academic staff. This work considered annual Key Performance Indicator Analysis data for the year 2020 with 53 sub parameters; this was from an engineering faculty for lecturers in two different grades with 12 and 27 samples, respectively. Eventually, there were 3 and 16 samples in grade DS45 and DS51/52, respectively, that have an insufficient time capacity. The remaining samples in both grades then had an unused time capacity, which ultimately resulted in unused cost capacity, also known as waste cost. This work was able to discover the total amount of used time that results in used, unused, or otherwise insufficient capacity, after analyzing the capacity cost using Time-Driven Activity-Based Costing.

Online Parallel-Batch Scheduling of Learning Effect Jobs with Incompatible Job Families for Prefabricated Components

In the production scheduling of prefabricated components, we study an online [Formula: see text] parallel-batch machines scheduling model considering learning effect jobs with [Formula: see text] incompatible job families to minimize the makespan in this paper, where the capacity of batch is unbounded. Job families indicate that a job must belong to some job family and jobs of distinct job families are incapable to be executed in the same batch. The information of each job including its basic processing time [Formula: see text] and release time [Formula: see text] is unknown in advance and is revealed at the instant of its arrival. Moreover, the actual processing time of job [Formula: see text] with learning effect is [Formula: see text], where [Formula: see text] and [Formula: see text] are non-negative parameters and [Formula: see text] denotes the starting time of prefabricated job [Formula: see text], respectively. When [Formula: see text], we propose an online algorithm with a competitive ratio of [Formula: see text]. Furthermore, the performance of the online algorithm is demonstrated by numerical experiments.

Resource Allocation Scheduling with Position-Dependent Weights and Generalized Earliness–Tardiness Cost

Under just-in-time production, this paper studies a single machine common due-window (denoted by CONW) assignment scheduling problem with position-dependent weights and resource allocations. A job’s actual processing time can be determined by the resource assigned to the job. A resource allocation model is divided into linear and convex resource allocations. Under the linear and convex resource allocation models, our goal is to find an optimal due-window location, job sequence and resource allocation. We prove that the weighted sum of scheduling cost (including general earliness–tardiness penalties with positional-dependent weights) and resource consumption cost minimization is polynomially solvable. In addition, under the convex resource allocation, we show that scheduling (resp. resource consumption) cost minimization is solvable in polynomial time subject to the resource consumption (resp. scheduling) cost being bounded.

Two-Agent Single Machine Scheduling with Deteriorating Jobs and Rejection

We consider two two-agent scheduling problems with deteriorating jobs and rejection. Two agents A and B compete for the usage of a single machine. The actual processing time of job J j X is p j X = b j X a + b t , X ∈ A , B , where b j X is the normal processing time of J j X , a ≥ 0 , b ≥ 0 and t denotes the starting time of J j X . A job is either rejected by paying a rejection penalty, or accepted and processed on the machine. The objective is to minimize the sum of the completion time of the accepted A -jobs and total rejection penalty of the rejected A -jobs subject to an upper bound on the sum of the given objective function f B of the accepted B -jobs and total rejection penalty of the rejected B -jobs, where f B ∈ C max B , ∑ C j B . We give dynamic programming algorithms for them, respectively. When f B = C max B , we present a fully polynomial-time approximation scheme (FPTAS) for the case a = 0 and b = 1 . When f B = ∑ C j B , a fully polynomial-time approximation scheme is also presented.

Taxonomy of Scheduling Problems with Learning and Deterioration Effects

In traditional scheduling problems, job processing times are considered constant and known in advance. This assumption is, however, a simplification when it comes to hand-intensive real-life production contexts because workers usually induce variability in the job processing times due to several factors such as learning, monotony, fatigue, psychological factors, etc. These effects can decrease or increase the actual processing time when workers execute a job. The academic literature has reported several modeling and resolution approaches to deal with the phenomenon in a variety of configurations. However, there is no comprehensive review of these research outputs to the best of our knowledge. In this paper, we follow a systematic approach to review relevant contributions addressing the scheduling problem with learning and deterioration effects. Modeling approaches for learning and deterioration effects, objective functions, and solution methods employed in the literature are the main topics for the taxonomy proposed in this review. A total of 455 papers from 1999 to 2021 are included and analyzed. Different areas of interest are presented, and some opportunities for future research are identified.

Japanese Pharmaceutical Regulations of Engineered Viral Vectors for Medical Use Compared With Those in the United States and the European Union.

Japanese Pharmaceutical Regulations of Engineered Viral Vectors for Medical Use Compared With Those in the United States and the European Union.

Implementation Of Lean Tool For Process Improvement Of Banking Services: A Case Study Of Regional Banks

Bank BJB continues to improve service quality by developing and strengthening banking services to customers. The current problems faced by Bank BJB are delays in service processes where the actual processing time exceeds the Service Level Agreement (SLA). The delay in the process is a non-value-added activity which is called waste. Aim This research aims to identify critical business processes of banking services that cause waste and improve using the Business Process Improvement method in the BJB Regional Treasury Branch. The research used the match method, data collection were obtained observation, interviews, and brainstorming with top management and users. Improvement using BPI was able to reduce the waiting time (queue) as waste and reduce lead time. The results of this study show the need for improvements to the tasks and functions of some parts such as Operational Service Officer, and Credit Officer so that more editions and no waste of time. So that the quality of service and customer satisfaction is achieved

Solving a stochastic hierarchical scheduling problem by VNS-based metaheuristic with locally assisted algorithms

High-end equipment manufacture has features of intensive technology, uncertain process, and large scale. Hence, the scheduling of the High-end equipment manufacture is challenging. Large ships are a type of High-end equipment that is tied to national maritime security. In this paper, we study a stochastic hierarchical scheduling problem with serial-batch processing machines and the deterioration effect in ship manufacture. In the studied problem, the job processing time is uncertain and follows a normal probability distribution. Under the deterioration effect, the actual processing time of jobs is formulated as a function of the start time. The first objective is to maximize the robustness of the manufacturing system. The second objective is to minimize the total inventory cost subjected to the optimization of the first objective. The robustness of the manufacturing system is measured by the worst level of completion probability. The total inventory cost is measured by the difference between the job delivery time and the job completion time. The mathematical model for the studied problem is formulated. Some structural properties are derived to solve the problem. Based on the properties, the optimal sequence for the first objective can be obtained and a heuristic algorithm is designed to optimize the second objective. The considered problem is NP-hard involving several non-linearities. Hence, a variable neighborhood search (VNS) algorithm is developed to solve the problem in a reasonable time, which is integrated with three local search strategies and a heuristic algorithm. Various problem instances are generated and extensive computational experiments verify that the proposed VNS algorithm outperforms other compared algorithms and has strong robustness.

Energy-efficient unrelated parallel machine scheduling with general position-based deterioration

ABSTRACT This paper investigates an energy-efficient scheduling problem on unrelated parallel machines considering general position-based deterioration which arises from the labour-intensive textile industry. The actual processing time of a job is not only associated with the job and the machine but also with its position in the processing sequence. The objective is to minimise the total energy consumption with a bounded makespan. To address this problem, we first establish a mixed-integer linear programming (MILP) model. Afterwards, the initial model is improved by deriving lower and upper bounds on the makespan, and an upper bound on the number of jobs processed on each machine. We also develop an iterative heuristic embedded with a variable neighbourhood search procedure (IHVNS). The algorithm obtains initial solutions iteratively by solving assignment problems and then repairs and improves them with the VNS procedure. Computational results demonstrate that the improved model is up to 230 times faster than the original one. Moreover, the proposed heuristic yields excellent solutions with average gaps of less than 0.73% for large-scale instances. Especially, the results reveal that the IHVNS algorithm is more suitable than MILP models for solving large-scale problems with tight makespan restrictions.

DEVELOPMENT A NEW COSTING STRUCTURE IN PRODUCT AND SERVICE OPERATION USING TIME DRIVEN ACTIVITY-BASED COSTING

In current practice of costing method in palm oil plantation, the method does not implement time equation so processing time determined by company is not in accordance with actual processing time in work station. Then, the present implementation in academic library do not illustrate the correlation between supplied resources and practical capacity. It is to develop capacity cost rate in order to interpret it in form of unused capacity. The purpose of this study is to build a new costing structure in product and service operation using time driven activity-based costing (TDABC). For product operation, this work carried on at a palm oil plantation in Prosper Palm Oil Mill Sdn. Bhd., Pahang. For service operation, data collection of academic library is taken in Universiti Malaysia Pahang. Eventually, in product operation, the total used time in all three activity centers of palm oil plantation are 3,220,928.04 minutes for mature area and 2,390,513.94 minutes for immature area. On the other hand, in service operation, the unused capacity is RM40,960.02 and RM144,202.51 in local and oversea material respectively. In terms of unused capacity, there are no significant differences when applying TDABC in product and service operation. Whereas, regarding of process dependency, activities in product operation are dependent to one another.

An optimal online algorithm for single-processor scheduling problem with learning effect

This paper deals with the canonical single-processor online scheduling problem with the position-based learning effect. Specially speaking, a round of jobs arriving online over time will be processed on a single processor. Noticeably, in this model, for each job Jk, the actual processing time pkl is defined as a power function of its position l, i.e., pkl=pklβ, where pk indicates its normal processing time and β≤0 is the learning index. Our goal is to make the sum of completion times as small as possible. For this problem, we testify that there is no online algorithm with a competitive ratio of less than 2. Most notably, we design an online algorithm entitled as Delayed Shortest Normal Processing Time (DSNPT), matching the lower bound proposed by us, and hence DSNPT is optimal.

Multi-project scheduling with multi-skilled workforce assignment considering uncertainty and learning effect for large-scale equipment manufacturer

This study addresses a resource-constrained multi-project scheduling and multi-skilled workforce assignment problem for the large-scale equipment manufacturing industry. The goal is to help the production manager perform effective planning and decrease the production cost under delivery constraints. The deterministic duration is used in most past investigations in resource-constrained multi-project scheduling problems. Uncertainty in project execution is neglected. Additional related factors are included in the current study to be close to practical circumstances. The required processing duration and material arrival time are modeled as stochastic variables. The heterogeneous skill efficiency of the internal workforce is considered with the learning effect. Skill efficiency grows with the accumulation of experience. Actual processing time is calculated on the basis of skill efficiency and stochastic process duration. The external workforce is hired when the internal workforce fails to satisfy processing demand. The objective is to minimize the expected integrated cost, which is the sum of tardiness penalty and external workforce cost. A genetic algorithm with a heuristic workforce assignment method is also developed, and a case study is illustrated to explain the scheduling result. The proposed approach with uniform crossover and local search mechanism outperforms other comparative methods by approximately 10.34% considering total costs. Furthermore, the Taguchi method of design of the experiment is conducted to find the optimal parameter setting efficiently. Afterward, the sensitivity analysis of production-related parameters is discussed.

The Due Window Assignment Problems with Deteriorating Job and Delivery Time

This paper considers the single machine scheduling problem with due window, delivery time and deteriorating job, whose goal is to minimize the window location, window size, earliness and tardiness. Common due window and slack due window are considered. The delivery time depends on the actual processing time of past sequences. The actual processing time of the job is an increasing function of the start time. Based on the small perturbations technique and adjacent exchange technique, we obtain the propositions of the problems. For common and slack due window assignment, we prove that the two objective functions are polynomial time solvable in O(nlogn) time. We propose the corresponding algorithms to obtain the optimal sequence, window location and window size.

Parallel-Machine Scheduling with Step-Deteriorating Jobs to Minimize the Total (Weighted) Completion Time

In this paper, we consider the parallel-machine scheduling with step-deteriorating jobs. The actual processing time of each job deteriorates as a step function if its starting time is beyond a given deteriorating date. We focus on the case of the common job deteriorating date. For the minimization problem of total completion time, we first show that the problem is NP-hard in the strong sense. Then we propose one property of any optimal schedule. Furthermore, we prove that two special cases of common normal processing time or common penalty are polynomially solvable. For the minimization problem of total weighted completion time, we analyze the NP-hardness and present a polynomial time optimal algorithm for the case of common normal processing time and common penalty.

Comparing linear and non-linear modelling approaches of learning effects in 2-stage flow-shop scheduling problems

Scheduling problems deal with the allocation and sequencing of a set of jobs to a set of production resources (machines, workers) to optimize one or more objective functions. In the literature, traditional deterministic approaches consider that processing times of jobs are fixed, constant and known at the initial time of scheduling. However, this assumption is not realistic particularly in hand-intensive manufacturing, where processing times may vary according to workers’ learning about the production process. To deal with this, this paper considers the problem of jobs scheduling with learning effect in the processing times. In contrast with previous works in the literature, it is not the processing time that changes per se, but the resource (worker) that improves his/her productivity by decreasing the actual job processing time. This paper considers the flow-shop configuration in which all jobs are processed by a set of different workers following the same production routing. It reviews linear and non-linear modelling approaches of the learning effect in processing times, in order to gain insights about the actual impact of such different modelling approaches. A computational comparison of exact solutions based on mathematical modelling of the flow-shop problem is presented for the case of two workers. Experiments were run using random-generated instances. Several insights are drawn regarding the behavior of the different models.